Machine Learning · GitHub

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LeetCode for PyTorch — 65 ML/AI interview problems from real interviews at Google, Meta, Anthropic. Jupyter notebooks, an auto-grader, and an MCP AI tutor.

🤗 The largest hub of ready-to-use datasets for AI models with fast, easy-to-use and efficient data manipulation tools

• 📦 One-line dataset loading - Load AI-ready datasets from the Hugging Face Hub or local files with load_dataset()
• 🔍 Multiple formats - Native support for CSV, JSON, JSONL, Parquet, Arrow, XML, Text, Webdataset, and more

Open Lakehouse Format for Multimodal AI. Convert from Parquet in 2 lines of code for 100x faster random access, vector index, and data versioning. Compatible with Pandas, DuckDB, Polars, Pyarrow, and PyTorch with more integrations coming..

JARVIS, a system to connect LLMs with the ML community. Paper: https://arxiv.org/pdf/2303.17580.pdf

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

CUDA Templates and Python DSLs for High-Performance Linear Algebra

A Python framework for GPU-accelerated simulation, robotics, and machine learning.

A hyperparameter optimization framework

• Handle a wide variety of tasks with a simple installation that has few requirements.
• Define search spaces using familiar Python syntax including conditionals and loops.

A curated list of Artificial Intelligence (AI) courses, books, video lectures and papers.

⚡️SwanLab - a modern-design AI training tracking and visualization tool under the Fair-code model. Supports cloud and self-hosted use. Integrates with PyTorch, Transformers, verl, LLaMA Factory, ms-swift, Ultralytics, MMEngine, Keras, and more.

Don't memorize ML. Understand it from first principles including Inference, Cuda, Deep Learning, Data Science and Reinforcement Learning

The world's simplest facial recognition api for Python and the command line

• Identify specific facial features in a photograph
• Apply (horribly ugly) digital make-up

Distributed GPU-Accelerated Framework for Evolutionary Computation. Comprehensive Library of Evolutionary Algorithms & Benchmark Problems.

Personal notes on Andrew Ng's machine learning course

🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch.

:sunrise: A comprehensive, cutting-edge open-source framework for next-generation Transformers, with compute-matched benchmarking and a platform for autonomous architecture research.

🐍 Geometric Computer Vision Library for Spatial AI

Pure Javascript OCR for more than 100 Languages 📖🎉🖥

TensorRT LLM provides users with an easy-to-use Python API to define Large Language Models (LLMs) and supports state-of-the-art optimizations to perform inference efficiently on NVIDIA GPUs. TensorRT LLM also contains components to create Python and C++ runtimes that orchestrate the inference execution in a performant way.