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Most people learn ML frameworks by importing them. We built ours by hand, then made it hit harder.

Build a modern LLM from scratch. Every line commented. Explained like we are five.

TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML-powered applications.

I implemented a transformer model from scratch using PyTorch, based on the paper Attention is All You Need. You can use my scripts to train your own billion or million parameter LLM using a single GPU.

PyTorch is a Python package that provides two high-level features: - Tensor computation (like NumPy) with strong GPU acceleration - Deep neural networks built on a tape-based autograd system

One day, frontier AI research used to be done by meat computers in between eating, sleeping, having other fun, and synchronizing once in a while using sound wave interconnect in the ritual of "group meeting". That era is long gone.

We then collect the + and and relu into a giant matmul, and either run it on JS or WebGPU, for fun.

Implementing LLM architectures from scratch in PyTorch

🆙 Upscayl - #1 Free and Open Source AI Image Upscaler for Linux, MacOS and Windows.

The goal is to help gamers get better image quality from the hardware they already own, particularly older and lower-end GPUs.

Update Nov 2025 nanoGPT has a new and improved cousin called nanochat. It is very likely you meant to use/find nanochat instead. nanoGPT (this repo) is now very old and deprecated but I will leave it up for posterity.

This package contains an OCR engine - libtesseract and a command line program - tesseract.

This application uses state-of-the-art source separation models to remove vocals from audio files. UVR's core developers trained all of the models provided in this package (except for the Demucs v3 and v4 4-stem models).

1 that analyzes chess positions and computes the optimal moves.

Fault-tolerant, highly scalable GPU orchestration, and a machine learning framework designed for training models with billions to trillions of parameters

Qdrant - High-performance, massive-scale Vector Database and Vector Search Engine for the next generation of AI. Also available in the cloud

A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API

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This update is also paired with a new Under the Hood transparency tool that allows people to see aggregate statistics about the labels on their account and posts that can limit visibility.

0, running FP8 on the tensor cores. The intermediates match too, not just the final image: all 75 block boundaries, byte for byte.

You input a raw green screen frame, and the neural network completely separates the foreground object from the green screen.

Note 1: For Windows, please install torch and torchvision first by following the official instructions here On the pytorch website, be sure to select the right CUDA version you have. If you intend to run on CPU mode only, select CUDA = None.

An opinionated, actively maintained collection of resources for software developers learning to build and ship generative AI and agentic systems.

Clone a voice in 5 seconds to generate arbitrary speech in real-time

Implemented the K-NN algorithm for classification. #100DaysOfMLCode Support Vector Machine Infographic is halfway complete. Will update it tomorrow.

Open Neural Network Exchange (ONNX) is an open ecosystem that empowers AI developers to choose the right tools as their project evolves. ONNX provides an open source format for AI models, both deep learning and traditional ML.

If you already have 1-year+ experience in machine learning, this course may help but it is specifically designed to be beginner-friendly.

深度学习入门教程, 优秀文章, Deep Learning Tutorial

spaCy is a library for advanced Natural Language Processing in Python and Cython. It's built on the very latest research, and was designed from day one to be used in real products.

These notebooks cover an introduction to deep learning, fastai, and PyTorch. fastai is a layered API for deep learning; for more information, see the fastai paper. Everything in this repo is copyright Jeremy Howard and Sylvain Gugger, 2020 onwards.