See and compare every AI model easily. 100% free & open-source.

2-week speedrun to machine learning mastery for either an engineer or researcher path.

A visualization of an MNIST neural network written from scratch in Odin and Raylib. This project provides a 3D visualisation of how a neural network works for the famous handwriting detection problem.

A visualization and walkthrough of LLM algorithm that backs OpenAI’s ChatGPT. Explore the algorithm down to every add & multiply, seeing the whole process in action.

A feed of noteworthy developments in AI.

A visual explanation of how generative AI works and how hallucinations occur.

Interactive deep learning book with code, math, and discussions. Implemented with PyTorch, NumPy/MXNet, JAX, and TensorFlow. Adopted at 500 universities from 70 countries.

This document aims to serve as a handbook for learning the key concepts underlying modern artificial intelligence systems. Given the speed of recent development in AI, there really isn’t a good textbook-style source for getting up-to-speed on the latest-and-greatest innovations in LLMs or other generative models, yet there is an abundance of great explainer resources (blog posts, videos, etc.) for these topics scattered across the internet. The goal is to organize the “best” of these resources into a textbook-style presentation, which can serve as a roadmap for filling in the prerequisites towards individual AI-related learning goals.