A WebGL accelerated JavaScript library for training and deploying ML models.
$ npx skills add tensorflow/tfjsAlternatives
Compare similar skills by workflow fit, trust score, quality, GitHub adoption, maintenance, and install readiness.
Current skill
Friendly machine learning for the web! 🤖
A WebGL accelerated JavaScript library for training and deploying ML models.
$ npx skills add tensorflow/tfjsA JavaScript deep learning and reinforcement learning library.
$ npx skills add janhuenermann/neurojsPublication-ready NN-architecture schematics.
$ npx skills add alexlenail/NN-SVGAn Open Source Machine Learning Framework for Everyone
$ npx skills add tensorflow/tensorflow⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 or handson-mlp instead.
$ npx skills add ageron/handson-mlPArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice (『飞桨』核心框架,深度学习&机器学习高性能单机、分布式训练和跨平台部署)
$ npx skills add PaddlePaddle/PaddleTensors and Dynamic neural networks in Python with strong GPU acceleration
$ npx skills add pytorch/pytorchOpen Machine Learning Compiler Framework
$ npx skills add apache/tvm🐍 Geometric Computer Vision Library for Spatial AI
$ npx skills add kornia/korniaVisualizer for neural network, deep learning and machine learning models
$ npx skills add lutzroeder/netronLearning Convolutional Neural Networks with Interactive Visualization.
$ npx skills add poloclub/cnn-explainer:alarm_clock: AI conference deadline countdowns
$ npx skills add paperswithcode/ai-deadlinesA flexible, high-performance serving system for machine learning models
$ npx skills add tensorflow/servingHigh-level library to help with training and evaluating neural networks in PyTorch flexibly and transparently.
$ npx skills add pytorch/igniteSupercharge Your Model Training
$ npx skills add mosaicml/composerRust bindings for the C++ api of PyTorch.
$ npx skills add LaurentMazare/tch-rsHow to choose
Use an alternative when it has a clearer install path, higher trust score, fresher maintenance, or better platform fit for your current agent stack. Keep Ml5 Library if it already passes your workflow test and repository review.
Next step
Open the compare page, test the install commands in a sandbox, and check each repository before using a skill in production.