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TensorFlow.js 是一个用于使用 JavaScript 进行机器学习开发的库

使用 JavaScript 开发机器学习模型,并直接在浏览器或 Node.js 中使用机器学习模型。

查看教程

教程将通过完整的端到端示例向您展示如何使用 TensorFlow.js。

查看模型

经过预先训练的开箱即用模型,适用于常见用例。

查看演示

使用 TensorFlow.js 在浏览器中运行的在线演示和示例。

工作原理

运行现有模型

使用现成的 JavaScript 模型或转换 Python TensorFlow 模型以在浏览器中或 Node.js 下运行。

重新训练现有模型

使用您自己的数据重新训练现有的机器学习模型。

使用 JavaScript 开发机器学习模型

使用灵活且直观的 API 直接用 JavaScript 构建和训练模型。

演示

性能 RNN

欣赏神经网络的现场钢琴演奏。

网络摄像头控制器

在浏览器中使用训练过的图像玩《吃豆人》游戏。

LipSync by YouTube

使用 Facemesh 在浏览器中实时对口型演唱热门歌曲《Dance Monkey》。

新闻和通告

欢迎查看我们的博客,了解其他动态;以及订阅 TensorFlow 每月简报,直接通过邮箱接收最新公告。

May 19, 2021  
Run TensorFlow Lite models on the web directly with TensorFlow.js

Unify your mobile and web ML deployments by reusing optimized TF Lite models and running in the browser via WebAssembly, no JavaScript rewrite required. Our new TF.js task APIs support a variety of models and backends.

May 18, 2021  
Speed-up your sites with web-page prefetching using ML

Improve website user experience by training a custom machine learning model with site navigation data to predict next pages, and use an Angular app to prefetch the content and improve site speed.

May 18, 2021  
Machine learning for next gen web apps with TensorFlow.js (Google I/O)

Get a high level overview of what TensorFlow.js is, how it's currently being used, what's new this year, plans for the future, and how you can get involved with our newly formed special interest and working groups.

Continue
May 17, 2021  
Next-generation pose detection with MoveNet

MoveNet is a human pose detection architecture designed to detect difficult poses and fast body motions. The model can run in the browser with very little latency, opening the door for a new class of applications and interactive experiences.