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
stable-diffusion-webui: Generate Images with Stable Diffusion
A Gradio-based web interface for generating and editing images with Stable Diffusion. It gives artists and other local users a browser-based workflow for prompts, image-to-image tools, model options, and extensions.
jax: Transform and Accelerate Python Numerical Programs
JAX is a Python library for transforming numerical programs with automatic differentiation, compilation, and vectorization. Use it for high-performance scientific computing and machine learning, especially when workloads need to scale across accelerators.
translation-agent: Improve Translations with an LLM Reflection Workflow
translation-agent is a Python demonstration that uses an LLM to translate text, review its own draft, and revise it. It suits experimentation with style, regional language, and terminology, but is not presented as mature production software.
index-tts-lora: Fine-Tune IndexTTS for Custom Voices
A Python project that adds LoRA fine-tuning workflows to IndexTTS for single- and multi-speaker voice synthesis. It is aimed at users who want to adapt speech generation to speaker audio and improve prosody and naturalness.
infinity: Serve Embedding and Reranking Models via API
Infinity is a Python serving engine for text embeddings, reranking, and selected image, audio, and late-interaction models. It provides an OpenAI-aligned REST API with multiple inference backends for teams deploying models from Hugging Face.
LLMBox: Train and Evaluate Large Language Models
LLMBox is a Python library for training and evaluating large language models through a unified pipeline. It suits researchers and developers who want configurable fine-tuning workflows and a broad set of model and benchmark evaluation options.
wifi-3d-fusion: Sense Motion with WiFi Signals
WiFi-3D-Fusion captures WiFi CSI or RSSI data and visualizes motion in 3D, with optional research bridges for pose estimation and RF field reconstruction. It is aimed at researchers and experimenters with compatible hardware, not production or safety-critical use.
sherpa-onnx: Run Speech AI Locally Across Platforms
sherpa-onnx runs speech and audio models locally through ONNX Runtime, without an internet connection. It supports tasks from speech recognition and synthesis to diarization, with APIs and deployment options spanning mobile, desktop, web, and embedded devices.
ML-From-Scratch: Learn Machine Learning Through NumPy Implementations
ML-From-Scratch provides transparent Python and NumPy implementations of machine learning algorithms, from regression and clustering to neural networks and reinforcement learning. It is suited to learners who want to inspect how models work rather than use an optimized production framework.
Waifu2x-Extension-GUI: Upscale Images and Video
A Windows desktop app for enlarging and denoising images, GIFs, and video, with AI-based video frame interpolation. It combines multiple processing engines and supports AMD, Nvidia, and Intel GPUs.
magenta-realtime: Generate Music Live from Prompts
Magenta RealTime 2 is an open-weights music generation model with Python and C++ inference options. It suits musicians and developers building live music tools, especially on Apple Silicon, with offline inference also available.
nudge: Fine-Tune Embeddings for Retrieval
NUDGE adjusts pre-computed document embeddings to improve retrieval without changing model parameters. It is designed for teams with labeled query-answer examples who want to optimize embeddings for search or RAG pipelines.