freeCodeCamp.org's open-source codebase and curriculum. Learn math, programming, and computer science for free.

Implement a ChatGPT-like LLM in PyTorch from scratch, step by step

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

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 lear…

⛔️ DEPRECATED – See https://github.com/ageron/handson-ml3 instead.

Inference Llama 2 in one file of pure C

Companion webpage to the book "Mathematics For Machine Learning"

Cut and paste your surroundings using AR

Python code for "Probabilistic Machine learning" book by Kevin Murphy

A Python-embedded modeling language for convex optimization problems.

Python library for converting Python calculations into rendered latex.

Open Deep Learning and Reinforcement Learning lectures from top Universities like Stanford, MIT, UC Berkeley.

AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.

Lectures for Udemy - Complete Python Bootcamp Course

Sionna: An Open-Source Library for Research on Communication Systems

Source code for the book Real-Time C++, by Christopher Kormanyos

Digital Communication with Python

Llama from scratch, or How to implement a paper without crying

Welcome to the official repository of SINQ! A novel, fast and high-quality quantization method designed to make any Large Language Model smaller while preserving accuracy.

Complete solutions to the Programming Massively Parallel Processors Edition 4

Summary, Code for Deep Neural Network Quantization

GPU accelerated decision optimization

[ICML 2023] Official PyTorch implementation of Global Context Vision Transformers

Fast low-bit matmul kernels in Triton

Implementation of Axial attention - attending to multi-dimensional data efficiently

Book PDF and simulation code for the monograph "Massive MIMO Networks: Spectral, Energy, and Hardware Efficiency" by Emil Björnson, Jakob Hoydis and Luca Sanguinetti, published in Foundations and T…

Measure and optimize the energy consumption of your AI applications!

Neural Networks with low bit weights on low end 32 bit microcontrollers such as the CH32V003 RISC-V Microcontroller and others

Code for the book "The Elements of Differentiable Programming".

A curated list of materials on AI efficiency