Popular GitHub Repositories for Distributed Algorithms

An Open Source Machine Learning Framework for Everyone

For developers, who are building real-time data-driven applications, Redis is the preferred, fastest, and most feature-rich cache, data structure server, and document and vector query engine.

Python ETL framework for stream processing, real-time analytics, LLM pipelines, and RAG.

100 Days of ML Coding

Learn how to design, develop, deploy and iterate on production-grade ML applications.

Making large AI models cheaper, faster and more accessible

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

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

:robot: The free, Open Source alternative to OpenAI, Claude and others. Self-hosted and local-first. Drop-in replacement for OpenAI, running on consumer-grade hardware. No GPU required. Runs gguf, transformers, diffusers and many more models architectures. Features: Generate Text, Audio, Video, Images, Voice Cloning, Distributed, P2P inference

GFPGAN aims at developing Practical Algorithms for Real-world Face Restoration.

The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more

Collection of various algorithms in mathematics, machine learning, computer science and physics implemented in C++ for educational purposes.

Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.

Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.

A complete daily plan for studying to become a machine learning engineer.

? Python examples of popular machine learning algorithms with interactive Jupyter demos and math being explained

PArallel Distributed Deep LEarning: Machine Learning Framework from Industrial Practice （『飞桨』核心框架，深度学习&机器学习高性能单机、分布式训练和跨平台部署）

Collection of various algorithms in mathematics, machine learning, computer science, physics, etc implemented in C for educational purposes.

Turns Data and AI algorithms into production-ready web applications in no time.

A fast, distributed, high performance gradient boosting (GBT, GBDT, GBRT, GBM or MART) framework based on decision tree algorithms, used for ranking, classification and many other machine learning tasks.