tfjs and TSTorch

These are competitors: TSTorch is an educational reimplementation of PyTorch concepts for WebGPU environments, while TensorFlow.js is the established production-grade library for the same use case of browser-based ML model training and inference.

tfjs
73
Verified
TSTorch
38
Emerging
Maintenance 13/25
Adoption 15/25
Maturity 25/25
Community 20/25
Maintenance 10/25
Adoption 7/25
Maturity 13/25
Community 8/25
Stars: 19,114
Forks: 2,022
Downloads:
Commits (30d): 1
Language: TypeScript
License: Apache-2.0
Stars: 39
Forks: 3
Downloads:
Commits (30d): 0
Language: TypeScript
License: MIT
No risk flags
No Package No Dependents

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.

web-development machine-learning-in-browser interactive-AI client-side-analytics javascript-AI

About TSTorch

r-chong/TSTorch

A PyTorch-style runtime library in TypeScript + WebGPU. Built to understand how ML frameworks and models work internally.

This is a machine learning library built from scratch in TypeScript, designed for those who want to understand the inner workings of ML frameworks. You can input data like numbers or arrays and define neural network structures using layers and activation functions. The output includes trained models capable of making predictions and insights into how automatic differentiation and tensor operations function. This tool is ideal for developers interested in learning about machine learning framework internals or building custom ML components in TypeScript.

machine-learning-frameworks deep-learning-development ml-engineering typescript-development computational-graph

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