TensorFlow.js 是可用 JavaScript 開發機器學習的程式庫
以 JavaScript 開發機器學習模型，並直接在瀏覽器或 Node.js 中使用機器學習。
運作方式
執行現有模型
使用現成的 JavaScript 模型或轉換 Python TensorFlow 模型，以便在瀏覽器作業或利用 Node.js 執行。
重新訓練現有模型
使用你自己的資料，重新訓練現有的機器學習模型。
以 JavaScript 開發機器學習
透過彈性且操作直覺的 API，直接使用 JavaScript 打造及訓練模型。
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.
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.
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.
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.
