Top MACHINE-LEARNING GitHub Repositories & Tools (2026)

Learn it. Build it. Ship it for others.

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

An Open Source Machine Learning Framework for Everyone

12 Weeks, 24 Lessons, AI for All!

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

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

🤗 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.

scikit-learn: machine learning in Python

Standardized Distributed Generative and Predictive AI Inference Platform for Scalable, Multi-Framework Deployment on Kubernetes

Tiny post-quantum encryption for sensitive data. Write-only by design. ML-KEM-768 + X25519 + AES-256-GCM. Please break it.

Dynamic, resilient AI orchestration. Coordinate data, models, and compute as you build AI workflows.

The fastest path to AI-powered full stack observability, even for lean teams.

Apache Airflow - A platform to programmatically author, schedule, and monitor workflows

The open-source System One decision model. Sub-15ms, non-autoregressive, local drop-in alternative to TypeSafe Jev.

RF-DETR is a real-time object detection and segmentation model architecture developed by Roboflow, SOTA on COCO, designed for fine-tuning. [ICLR 2026]

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.

Ray is an AI compute engine. Ray consists of a core distributed runtime and a set of AI Libraries for accelerating ML workloads.

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

Refine high-quality datasets and visual AI models

Audio Plugin for Audio to MIDI transcription using deep learning.