amazon_us_reviews

सन्दर्भ:

• कोड
• हगिंगफेस

पुस्तकें_v1_01

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Books_v1_01')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	6106719

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

घड़ियाँ_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Watches_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	960872

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Personal_Care_Appliances_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Personal_Care_Appliances_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	85981

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

मोबाइल_इलेक्ट्रॉनिक्स_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Mobile_Electronics_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	104975

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

डिजिटल_वीडियो_गेम_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Digital_Video_Games_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	145431

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

डिजिटल_सॉफ्टवेयर_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Digital_Software_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	102084

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

प्रमुख_उपकरण_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Major_Appliances_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	96901

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

गिफ्ट_कार्ड_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Gift_Card_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	149086

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

वीडियो_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Video_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	380604

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

सामान_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Luggage_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	348657

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

सॉफ्टवेयर_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Software_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	341931

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

वीडियो_गेम_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Video_Games_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	1785997

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

फर्नीचर_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Furniture_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	792113

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Musical_Instruments_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Musical_Instruments_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	904765

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Digital_Music_Purchase_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Digital_Music_Purchase_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	1688884

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

पुस्तकें_v1_02

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Books_v1_02')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	3105520

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

होम_मनोरंजन_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Home_Entertainment_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	705889

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

किराना_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Grocery_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	2402458

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

आउटडोर_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Outdoors_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	2302401

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

पेट_उत्पाद_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Pet_Products_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	2643619

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

वीडियो_डीवीडी_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Video_DVD_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	5069140

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

परिधान_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Apparel_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	5906333

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

पीसी_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/PC_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	6908554

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

टूल्स_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Tools_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	1741100

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

आभूषण_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Jewelry_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	1767753

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

बेबी_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Baby_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	1752932

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

होम_सुधार_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Home_Improvement_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	2634781

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

कैमरा_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Camera_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	1801974

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

लॉन_और_गार्डन_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Lawn_and_Garden_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	2557288

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

कार्यालय_उत्पाद_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Office_Products_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	2642434

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

इलेक्ट्रॉनिक्स_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Electronics_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	3093869

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

ऑटोमोटिव_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Automotive_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	3514942

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

डिजिटल_वीडियो_डाउनलोड_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Digital_Video_Download_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	4057147

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Mobile_Apps_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Mobile_Apps_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	5033376

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

जूते_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Shoes_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	4366916

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

खिलौने_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Toys_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	4864249

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

खेल_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Sports_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	4850360

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

रसोई_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Kitchen_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	4880466

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

सौंदर्य_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Beauty_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	5115666

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

संगीत_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Music_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	4751577

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Health_Personal_Care_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Health_Personal_Care_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	5331449

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Digital_Ebook_Purchase_v1_01

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Digital_Ebook_Purchase_v1_01')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	5101693

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

होम_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Home_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	6221559

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

वायरलेस_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Wireless_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	9002021

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

पुस्तकें_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Books_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	10319090

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}

Digital_Ebook_Purchase_v1_00

इस डेटासेट को TFDS में लोड करने के लिए निम्न कमांड का उपयोग करें:

ds = tfds.load('huggingface:amazon_us_reviews/Digital_Ebook_Purchase_v1_00')

• विवरण :

Amazon Customer Reviews (a.k.a. Product Reviews) is one of Amazons iconic products. In a period of over two decades since the first review in 1995, millions of Amazon customers have contributed over a hundred million reviews to express opinions and describe their experiences regarding products on the Amazon.com website. This makes Amazon Customer Reviews a rich source of information for academic researchers in the fields of Natural Language Processing (NLP), Information Retrieval (IR), and Machine Learning (ML), amongst others. Accordingly, we are releasing this data to further research in multiple disciplines related to understanding customer product experiences. Specifically, this dataset was constructed to represent a sample of customer evaluations and opinions, variation in the perception of a product across geographical regions, and promotional intent or bias in reviews.

Over 130+ million customer reviews are available to researchers as part of this release. The data is available in TSV files in the amazon-reviews-pds S3 bucket in AWS US East Region. Each line in the data files corresponds to an individual review (tab delimited, with no quote and escape characters).

Each Dataset contains the following columns:

- marketplace: 2 letter country code of the marketplace where the review was written.
- customer_id: Random identifier that can be used to aggregate reviews written by a single author.
- review_id: The unique ID of the review.
- product_id: The unique Product ID the review pertains to. In the multilingual dataset the reviews for the same product in different countries can be grouped by the same product_id.
- product_parent: Random identifier that can be used to aggregate reviews for the same product.
- product_title: Title of the product.
- product_category: Broad product category that can be used to group reviews (also used to group the dataset into coherent parts).
- star_rating: The 1-5 star rating of the review.
- helpful_votes: Number of helpful votes.
- total_votes: Number of total votes the review received.
- vine: Review was written as part of the Vine program.
- verified_purchase: The review is on a verified purchase.
- review_headline: The title of the review.
- review_body: The review text.
- review_date: The date the review was written.

• लाइसेंस : कोई ज्ञात लाइसेंस नहीं
• संस्करण : 0.1.0
• विभाजन :

विभाजित करना	उदाहरण
'train'	12520722

• विशेषताएं :

{
    "marketplace": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "customer_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_id": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_parent": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_title": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "product_category": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "star_rating": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "helpful_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "total_votes": {
        "dtype": "int32",
        "id": null,
        "_type": "Value"
    },
    "vine": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "verified_purchase": {
        "num_classes": 2,
        "names": [
            "N",
            "Y"
        ],
        "id": null,
        "_type": "ClassLabel"
    },
    "review_headline": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_body": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    },
    "review_date": {
        "dtype": "string",
        "id": null,
        "_type": "Value"
    }
}