TensorFlow.js Best Practices

Comprehensive best practices guide for TensorFlow.js applications, designed for AI agents and LLMs. Contains 30+ rules across 7 categories, prioritized by impact to guide code generation, review, and refactoring.

When to Apply

Reference these guidelines when:

• Writing new TensorFlow.js code (browser, Node.js, or React Native)
• Creating or loading ML models with TF.js APIs
• Implementing data preprocessing pipelines with tf.data or tf.tensor
• Optimizing inference or training performance
• Running .tflite models in the browser with LiteRT.js
• Debugging memory leaks, slow inference, or numerical issues
• Choosing between WebGL, WASM, WebGPU, or Node.js backends

Rule Categories by Priority