tfjs and tfjs-core
TensorFlow.js is a high-level library that depends on tfjs-core as its underlying engine, providing the WebGL acceleration and autodiff primitives while tfjs-core handles the low-level tensor operations and GPU computation.
About tfjs
tensorflow/tfjs
A WebGL accelerated JavaScript library for training and deploying ML models.
TensorFlow.js helps web developers build and run machine learning models directly in web browsers or Node.js applications. It takes raw data, pre-trained TensorFlow or Keras models, and outputs interactive ML experiences without server-side processing. This allows front-end developers and web application builders to integrate AI capabilities into their projects.
About tfjs-core
tensorflow/tfjs-core
WebGL-accelerated ML // linear algebra // automatic differentiation for JavaScript.
Provides GPU-accelerated tensor operations and computational graph differentiation through WebGL, with CPU fallback support. Implements eager execution for dynamic computation graphs while maintaining automatic gradient computation for training neural networks. Integrates as the core numeric engine for TensorFlow.js, enabling in-browser ML inference and training across multiple backends.
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