microsoft / ML-For-Beginners

A 12-week, 26-lesson beginner curriculum on classic machine learning using Scikit-learn, with quizzes and projects in Python and R.

ageron / handson-ml3

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, Keras and TensorFlow 2.

ageron / handson-mlp

A series of Jupyter notebooks that walk you through the fundamentals of Machine Learning and Deep Learning in Python using Scikit-Learn, PyTorch, and Hugging Face libraries.

microsoft / FLAML

A fast library for AutoML and tuning. Join our Discord: https://discord.gg/Cppx2vSPVP.

scikit-learn-contrib / MAPIE

A scikit-learn-compatible library for estimating prediction intervals and controlling risks, based on conformal predictions.

skorch-dev / skorch

A scikit-learn compatible neural network library that wraps PyTorch

dusty-nv / jetson-containers

Machine Learning Containers for NVIDIA Jetson and JetPack-L4T

scikit-learn-contrib / hdbscan

A high performance implementation of HDBSCAN clustering.

csinva / imodels

Interpretable ML package 🔍 for concise, transparent, and accurate predictive modeling (sklearn-compatible).

INRIA / scikit-learn-mooc

Machine learning in Python with scikit-learn MOOC

hamza01055 / ml-from-scratch

Machine learning from scratch with Python and NumPy. Explore 12 chapters covering regression, neural networks, trees, clustering, SVMs, and autodiff with mathematical derivations, interactive notebooks, gradient verification, and 59 automated tests. No scikit-learn or PyTorch.