Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Core deep-learning frameworks and libraries for pretraining and distributed training.
Signals: deep-learning, neural-network, pytorch, tensorflow, jax, distributed-training, training, deepspeed
2,663 results
Modeltime unlocks time series forecast models and machine learning in one framework
Massively parallel training of machine-learning based weather and climate models
Bug-free machine learning on stochastic computation graphs
Traditional machine learning on top of Nx
Trident-ML : A realtime online machine learning library
🍧 DataCamp data-science and machine learning courses
Lightwood is Legos for Machine Learning.
Machine learning for C# .Net
Machine Learning for .NET
Arm Machine Learning tutorials and examples
Repository for the "Machine Learning for the Web" class at ITP, NYU
✨ AI/ML Research
Setup end to end demo architecture for predicting fraud events with Machine Learning using Amazon SageMaker
Complete path for a beginner to become a Machine Learning Scientist!
常见的机器学习参考资料，包括书籍、公开课等
my machine-learning tutorial
Machine Learning Lectures at the European Space Agency (ESA) in 2018
Otto makes machine learning an intuitive, natural language experience. 🏆 Facebook AI Hackathon winner ⭐️ #1 Trending on MadeWithML.com ⭐️ #4 Trending JavaScript Project on GitHub ⭐️ #15 Trending (All Languages) on GitHub
ML-capsule is a Project for beginners and experienced data science Enthusiasts who don't have a mentor or guidance and wish to learn Machine learning. Using our repo they can learn ML, DL, and many related technologies with different real-world projects and become Interview ready.
A machine learning library with a TypeScript API and Rust backend. CUDA and WebGPU compatibility. Built to understand how ML frameworks and models work internally.
Implementation/Tutorial of using Automated Machine Learning (AutoML) methods for static/batch and online/continual learning
Feature engineering is the process of using domain knowledge to extract features from raw data via data mining techniques. These features can be used to improve the performance of machine learning algorithms. Feature engineering can be considered as applied machine learning itself.
A comprehensive set of fairness metrics for datasets and machine learning models, explanations for these metrics, and algorithms to mitigate bias in datasets and models.
Cookiecutter template for FastAPI projects using: Machine Learning, uv, Github Actions and Pytests
24,545 repositories in the index in total.
