Machine Learning GitHub Repositories (2026) · Open Source Tools

Learn AI Engineering! Learn it. Build it. Ship it for others.

Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

12 Weeks, 24 Lessons, AI for All!

🤗 Transformers: the model-definition framework for state-of-the-art machine learning models in text, vision, audio, and multimodal models, for both inference and training.

Audio Plugin for Audio to MIDI transcription using deep learning.

The #1 AI Harness for Building Resumes, PDFs, Cover Letters & more, locally with 100+ LLMs support.

Fine-tune LLMs from one YAML. Layer streaming trains an 8B model on a 4 GB laptop GPU.

scikit-learn: machine learning in Python

Native MLX runtime for Laya typed decision models — 7–14 ms short decisions on M3 Max. No text generation, PyTorch, or cloud API.

A community-supported supercharged document management system: scan, index and archive all your documents

Streamlit — A faster way to build and share data apps.

Cross-platform, customizable ML solutions for live and streaming media.

A reactive notebook for Python — run reproducible experiments, query with SQL, execute as a script, deploy as an app, and version with git. Stored as pure Python. All in a modern, AI-native editor.

Build and share delightful machine learning apps, all in Python. 🌟 Star to support our work!

Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud https://cloud.qdrant.io/

⚡ TabPFN: Foundation Model for Tabular Data ⚡

Finathink — Financial Research Optimizer for auditable, point-in-time research, mathematical learning, and constrained portfolio analysis.

A brain that learns from live experience. System 1 by default: perception, memory, plasticity and action. Optional System 2 for self-observation and slow corrections.

A Lightweight Face Recognition and Facial Attribute Analysis (Age, Gender, Emotion and Race) Library for Python

Type-safe, distributed orchestration of agents, ML pipelines, and real-time inference on your k8s — in pure Python with async/await, also other languages (rust, go and ts)