The most cited deep learning papers

Latex code for making neural networks diagrams

The Linux Kernel Module Programming Guide (updated for 5.0+ kernels)

Classical equations and diagrams in machine learning

Course materials for Georgia Tech CS 4650 and 7650, "Natural Language"

A comprehensive 10-page probability cheatsheet that covers a semester's worth of introduction to probability.

📙 The probability and statistics cookbook

A high-speed network driver written in C, Rust, C++, Go, C#, Java, OCaml, Haskell, Swift, Javascript, and Python

Clever Algorithms: Nature-Inspired Programming Recipes

The Standard DAO Framework, including Whitepaper

Internet of Blockchains ⚛

An open-source, customizable intermediate logic textbook

Book in preparation: introduction to theoretical computer science

Quicksheet for Algorithms

Large language Models (LLM)

Slides for my machine learning course based on Sebastian Raschka's Python Machine Learning book

A concise Julia language introductory manual for programmers.

📖 My reading list of academic papers and research notes

A Julia tutorial

Material for some talks I have given

Sources for algorithm selection for combinatorial search problems survey

Sources of my PhD thesis circa 2008 at Université Blaise Pascal (Clermont-Ferrand, France) and UNSW (Sydney, Australia)