库和扩展程序
探索使用 TensorFlow 构建高级模型或方法的库，并访问可针对特定领域扩展 TensorFlow 的应用软件包。
-
查看文档Extra functionality for TensorFlow, maintained by SIG Addons.
TensorFlow Addons
-
查看文档A library for designing, testing, and implementing reinforcement learning algorithms.
TensorFlow Agents
-
查看文档A library to build ML models with end-to-end optimized data compression built in.
TensorFlow Compression
-
查看文档A library to analyze training and serving data to compute descriptive statistics, infer schemas, and detect anomalies.
TensorFlow Data Validation
-
查看文档State-of-the-art algorithms for training, serving and interpreting models that use decision forests for classification, regression and ranking.
TensorFlow Decision Forests
-
A research framework for fast prototyping of reinforcement learning algorithms.
Dopamine
-
查看文档A library that enables easy computation of commonly-identified fairness metrics for binary and multiclass classifiers.
Fairness Indicators
-
查看文档An open source framework for machine learning and other computations on decentralized data.
TensorFlow Federated
-
A library to build neural networks on graph data (nodes and edges with arbitrary features), including tools for preparing input data and training models.
TensorFlow GNN
-
查看文档A library of computer graphics functionalities ranging from cameras, lights, and materials to renderers.
TensorFlow Graphics
-
查看文档A library for reusable machine learning. Download and reuse the latest trained models with a minimal amount of code.
TensorFlow Hub
-
查看文档Dataset, streaming, and file system extensions, maintained by SIG IO.
TensorFlow IO
-
查看文档Language bindings for Java and other JVM languages, such as Scala or Kotlin.
TensorFlow JVM
-
A library of modular components for common computer vision tasks such as data augmentation, classification, object detection, segmentation, and more.
KerasCV
-
An easily customizable natural language processing library providing modular components and state-of-the-art preset weights and architectures.
KerasNLP
-
查看文档A library for flexible, controlled and interpretable ML solutions with common-sense shape constraints.
TensorFlow Lattice
-
查看文档A library to run ML models on digital signal processors (DSPs), microcontrollers, and other devices with limited memory.
TensorFlow Lite Micro
-
查看文档A library that simplifies model training for on-device natural language processing, vision, and audio applications.
TensorFlow Lite Model Maker
-
查看文档A toolkit to customize model interface on Android, create metadata, and build inference pipelines for mobile deployment.
TensorFlow Lite Support
-
Utilities for passing TensorFlow-related metadata between tools.
TensorFlow Metadata
-
查看文档A library for recording and retrieving MLOps metadata associated with machine learning workflows.
ML Metadata
-
查看文档A library for deep analysis of model results beyond simple training metrics, to measure edge and corner cases and bias.
TensorFlow Model Analysis
-
查看文档A collection of tools to generate documents that provide context and transparency into a model's development and performance.
Model Card Toolkit
-
查看文档A suite of tools for optimizing ML models for deployment and execution.
Model Optimization Toolkit
-
查看文档A library to help create and train models in a way that reduces or eliminates user harm resulting from underlying performance biases.
TensorFlow Model Remediation
-
Utilities for manipulating data in a n-dimensional space in Java, maintained by SIG JVM.
NdArray
-
查看文档A learning framework to train neural networks by leveraging structured signals in addition to feature inputs.
Neural Structured Learning
-
查看文档A Python library that includes implementations of TensorFlow optimizers for training machine learning models with differential privacy.
TensorFlow Privacy
-
查看文档A library for probabilistic reasoning and statistical analysis.
TensorFlow Probability
-
查看文档A quantum machine learning library for rapid prototyping of hybrid quantum-classical ML models.
TensorFlow Quantum
-
查看文档A library for Learning-to-Rank (LTR) techniques on the TensorFlow platform.
TensorFlow Ranking
-
查看文档A library for building recommender system models.
TensorFlow Recommenders
-
A collection of community projects introducing Dynamic Embedding Technology to large-scale recommendation systems built upon TensorFlow
TensorFlow Recommenders Addons
-
查看文档A flexible, high-performance serving system for machine learning models, designed for production environments
TensorFlow Serving
-
A library from DeepMind for constructing neural networks.
Sonnet
-
查看文档A collection of text- and NLP-related classes and ops ready to use with TensorFlow 2.
TensorFlow Text
-
查看文档A library for large-scale feature engineering and eliminating training-serving skew.
TensorFlow Transform
-
查看文档A hardware-accelerated library for training and deploying ML models using JavaScript or Node.js.
TensorFlow.js
-
查看文档An end-to-end platform for deploying production ML pipelines.
TFX
-
查看文档A collection of community projects to build new components, examples, libraries, and tools for TFX.
TFX-Addons