Open Source Machine Learning Projects
Discover 191 open source Machine Learning repositories from GitHub, each with an analysis of what it does, key features, use cases and alternatives. Machine Learning projects here are most often combined with Python, Deep Learning and LLM. Last updated October 4, 2026.
191 repositories · updated October 4, 2026
rag-from-scratch: Learn Retrieval-Augmented Generation Step by Step
A Jupyter notebook series that teaches the building blocks of retrieval-augmented generation, from indexing and retrieval to generation. It is aimed at learners who want to understand RAG concepts through an educational progression rather than adopt a ready-made application.
StreamingKokoroJS: Generate Speech Locally in Your Browser
StreamingKokoroJS turns text into speech in the browser with the Kokoro-82M model. It streams audio locally, with WebGPU acceleration when available and a WebAssembly fallback, without sending text to a server.
chatterbox: Generate Speech from Text with Voice Cloning
Chatterbox is Resemble AI’s Python text-to-speech model family, with English and multilingual options, voice cloning, and expressive speech controls. It suits developers building voice experiences who can manage model inference and its compute requirements.
Kimi-k1.5: Train Multimodal LLMs with Reinforcement Learning
Kimi k1.5 is a research project describing reinforcement learning methods for training long-context, multimodal language models. It is aimed at researchers studying LLM reasoning and training, rather than users looking for a ready-to-install model.
judges: Evaluate LLM Outputs with Reusable AI Judges
Databricks judges is a Python library for evaluating language model outputs with reusable LLM-based classifiers and graders. Use its research-backed judges, combine evaluations with a jury, or build a custom judge for your task.
CompreFace: Run Self-Hosted Face Recognition APIs
CompreFace is a Docker-based face analysis service with REST APIs for recognition, verification, detection, and related tasks. It suits teams that need to integrate face processing into applications while keeping deployment on their own infrastructure.
co-tracker: Track Points Across Video Frames
CoTracker tracks selected or grid-sampled points through video using a transformer-based model. It offers offline and online inference, pretrained checkpoints, and tools for evaluation and training.
pyAudioAnalysis: Extract Features and Analyze Audio in Python
pyAudioAnalysis is a Python library for extracting audio features and building classification, detection, and segmentation workflows. It suits researchers and developers who want an established toolkit for analyzing audio files with machine-learning methods.
notebooks: Learn and Apply Computer Vision Models
Roboflow notebooks is a hands-on tutorial collection for computer vision, covering model training, inference, detection, segmentation, and related tasks. Use it to explore techniques and run examples in hosted notebook environments.
Spark-TTS: Generate Speech and Clone Voices from Text
Spark-TTS is a PyTorch inference project for bilingual text-to-speech and zero-shot voice cloning. It uses a Qwen2.5-based model to generate speech and supports adjustable voice characteristics.
TRELLIS: Generate 3D Assets from Text or Images
TRELLIS is a research model and toolkit for generating 3D assets from text or images. Its structured latent representation can produce meshes, 3D Gaussians, and radiance fields, but local use requires a compatible NVIDIA GPU and a substantial setup.
AudioSep: Separate Sounds from Natural-Language Descriptions
AudioSep is a Python foundation model for separating sounds from audio based on natural-language descriptions. It supports open-domain tasks such as isolating events, instruments, or speech, with inference, fine-tuning, and evaluation workflows.