Computer Games AI

• Programming Starcraft AI
• Artificial Intelligence and Games
• Artificial Intelligence and Games
• Game AI Pro
• Programming Starcraft AI

Machine Learning

• Data-Driven Science and Engineering: Machine Learning, Dynamical Systems, and Control
• Deep Learning
• Deep Learning Course
• Deep Learning: Foundations and Concepts
• Dive into Deep Learning Compiler
• Information Theory, Inference, and Learning Algorithms
• Mathematical Introduction to Deep Learning: Methods, Implementations, and Theory
• Mathematics for Machine Learning
• Neural Networks: Zero to Hero - A course by *Andrej Karpathy*
• Physics-based Deep Learning
• Probabilistic Machine Learning: An Introduction
• Probabilistic Machine Learning: Advanced Topics
• The Little Book of Deep Learning
• Learning Theory from First Principles
• Speech and Language Processing, 3rd edition
• The Elements of Differentiable Programming
• Alice’s Adventures in a differentiable wonderland
• Crash Course in Deep Learning (for Computer Graphics)
• The Engineer's Guide To Deep Learning
• Applied Machine Learning for Tabular Data
• Deep Learning Interviews
• A Course in Machine Learning
• Deep Reinforcement Learning: Zero to Hero!
• Machine Learning Engineering Book
• Machine Learning Engineering Open Book
• A Comprehensive Guide to Machine Learning
• Algorithmic Aspects of Machine Learning
• An Illustrated Guide to Automatic Sparse Differentiation
• Concise Machine Learning
• Data Science and Machine Learning: Mathematical and Statistical Methods
• Deep Learning on Graphs
• Deep Learning with Python, Second Edition
• Dummy's Guide to Modern LLM Sampling
• Foundations of Computer Vision
• Harvard's undergraduate course in Machine Learning
• Introduction to Flow Matching and Diffusion Models
• Introduction to ggml
• Introduction to Machine Learning
• Introduction to Machine Learning
• Introduction to Machine Learning
• Lecture Notes for Machine Learning and Data Science Courses Information School, University of Washington
• Lecture Notes for Machine Learning Theory
• Machine Learning Lecture Notes
• Machine learning with neural networks
• Notes on AutoGrad
• Probabilistic Artificial Intelligence
• Statistical Learning Theory
• The Most Important Machine Learning Equations: A Comprehensive Guide
• The Principles of Deep Learning Theory
• The Principles of Diffusion Models: From Origins to Advances - Hsin Lai*, *Yang Song*, *Dongjun Kim*, *Yuki Mitsufuji*, *Stefano Ermon*
• Theory of Deep Learning
• Tutorial on Diffusion Models for Imaging and Vision
• A Visual Guide to Quantization: Demystifying the Compression of Large Language Models
• Foundations of Large Language Models
• How to run LLMs on PC at home using Llama.cpp
• Google Machine Learning Education
• Linear Algebra for Computer Vision, Robotics, and Machine Learning
• Mathematical Analysis of Machine Learning Algorithms
• Mathematical Foundations of Machine Learning
• Mathematics for Machine Learning
• Mathematics for Inference and Machine Learning
• Mathematics of Machine Learning
• Mathematics of Machine Learning
• Mathematics of Neural Networks
• Matrix Calculus (for Machine Learning and Beyond)
• MIT course
• GitHub repository
• Optimization for Data Science
• Pen and Paper Exercises in Machine Learning
• The Matrix Calculus You Need For Deep Learning
• Deep Reinforcement Learning
• Mathematical Foundations of Reinforcement Learning
• Reinforcement Learning: An Introduction, Second Edition
• Reinforcement Learning: An Overview
• GNN From Scratch
• Understanding Machine Learning: From Theory to Algorithms - Shwartz* and *Shai Ben-David*
• Data Science and Machine Learning: Mathematical and Statistical Methods
• Machine Learning Systems
• Algorithms for Artificial Intelligence
• LLM Inference Handbook
• Quantization from the ground up
• A Brief Introduction to Machine Learning for Engineers
• A Brief Introduction to Neural Networks
• The Big Book of Large Language Models
• Applied Causal Inference Powered by ML and AI
• Deep Learning
• Version with Python and R
• Natural Language Processing
• The Little Book of Generative AI Foundations: An Intuitive Mathematical Primer
• Language Models Interview Handbook
• LLM Inference Handbook
• Deep Learning: Foundations, Architectures, and Engineering Practice
• A Course in Machine Learning
• A Gentle Introduction to Graph Neural Networks - Lengeling*, *Emily Reif*, *Adam Pearce* and *Alexander B. Wiltschko*
• Alice’s Adventures in a differentiable wonderland
• An Illustrated Guide to Automatic Sparse Differentiation
• An Introduction to Statistical Learning
• Applied Machine Learning for Tabular Data
• The Hundred Page Machine Learning Book
• Machine Learning Engineering Book
• Computer Vision: Algorithms and Applications, 2nd Edition
• Deep Learning
• Version with Python and R
• Deep Learning Course
• Deep Learning: Foundations and Concepts
• Deep Learning on Graphs
• Dive into Deep Learning
• Foundations of Computer Vision
• Foundations of Machine Learning
• Introduction to Flow Matching and Diffusion Models
• Introduction to Machine Learning Interviews
• Introduction to Machine Learning Systems
• Patterns, Predictions, and Actions: A story about machine learning
• The Elements of Statistical Learning
• The Engineer's Guide To Deep Learning
• The Little Book of Deep Learning
• The Most Important Machine Learning Equations: A Comprehensive Guide
• Understanding Deep Learning
• How to Scale Your Model: A Systems View of LLMs on TPUs
• LLM Inference Handbook
• The Big Book of Large Language Models
• Mathematics for Artificial Intelligence Lecure Notes
• Mathematics of Machine Learning
• MIT course
• The Matrix Calculus You Need For Deep Learning
• A Little Bit of Reinforcement Learning from Human Feedback
• Deep Reinforcement Learning
• Distributional Reinforcement Learning
• Multi-Agent Reinforcement Learning: Foundations and Modern Approaches

Vibe Coding and Spec-Driven Development

• Basic Claude Code
• Disciplined AI Software Development
• Diving Into Spec-Driven Development With GitHub Spec Kit
• How I program with Agents
• How I program with LLMs
• How I Use Every Claude Code Feature
• My LLM codegen workflow atm
• Spec-driven development with AI: Get started with a new open source toolkit
• Vibe Coding Terminal Editor
• AI-Assisted Coding: A Practical Guide for Software Engineers
• AI-Assisted Coding: A Practical Guide for Software Engineers
• Basic Claude Code
• My LLM codegen workflow atm
• Spec-driven development with AI: Get started with a new open source toolkit

• Paradigms of Artificial Intelligence Programming: Case Studies in Common Lisp
• Agentic Design Patterns
• Maths, CS & AI Compendium
• Paradigms of Artificial Intelligence Programming: Case Studies in Common Lisp

Bloom Filters

• Bloom Filters
• Let's implement a Bloom Filter
• Bloom Filters by Example
• Let's implement a Bloom Filter

Computer Games AI

• Foundations of Data Science
• Algorithms
• Algorithms and Data Structures
• Algorithms for Optimization
• The Arcane Algorithm Archive
• Competitive Programming Algorithms
• Competitive Programmer's Handbook
• Exact String Matching Algorithms
• How does B-tree make your queries fast?
• Introduction to Algorithms: A Creative Approach
• Planning Algorithms
• Principles of Algorithmic Problem Solving
• Purely Functional Data Structures
• Sequential and Parallel Data Structures and Algorithms: The Basic Toolbox
• Collision Detection
• Data Structures for Data-Intensive Applications: Tradeoffs and Design Guidelines
• Monte-Carlo Graph Search from First Principles

Date-time

• A Very Fast 64–Bit Date Algorithm

Diff Algorithms

• Part 1
• Part 2
• Part 3
• Part 1: Theory
• Part 2: Implementation
• Merging with diff3
• Why merges fail and what can be done about it
• The patience diff algorithm
• Implementing patience diff
• Diff Algorithms
• Myers Diff Algorithm - Code & Interactive Visualization
• Part 1
• Part 2
• Part 3
• Part 1: Theory
• Part 2: Implementation
• Merging with diff3
• Why merges fail and what can be done about it
• The patience diff algorithm
• Implementing patience diff
• Diff Algorithms

Vibe Coding and Spec-Driven Development

• A First Course on Data Structures in Python
• Advanced Algorithms
• Advanced Algorithms
• Advanced Algorithms
• Advanced Algorithm Design