HenryNdubuaku/maths-cs-ai-compendium

Курс-шпаргалка по математике для ИИ и ML 2026: линейая алгебра, матанализ, оптимизация, вероятности, стаистика, теория информации, трансформеры, диффузия, LM. Формулы, картинки, код, 40 задач, 100 вопросов

🥸 Math 🤡 Machine 🥶 Learning 🤖 is a structured 🤑 mathematical 🦁 🚞foundations 🦊 essential 🦫 AI ML linear 🐲 algebra 🐸 probability 🐊 🛬calculus 🐳 🛼optimization 🦋 bridges 🐙 the gap 🥯 between 🍊theory 🚟practical 🍏 implementation 🍑 in Python 🥭 making 🍔 understand 🍱 the math ✈ that powers 🚀 modern machine learning algorithms

Machine Learning Systems: Foundations, Scaling, Agentic AI, and Physical AI (Vols I–IV) • Harvard CS249r | https://mlsysbook.ai

Master the fundamentals of machine learning, deep learning, and mathematical optimization by building key concepts and models from scratch using Python.

The AI Compendium, previously called the ML Compendium, curates resources and explanations of machine learning (ML) and deep learning, from a business problem through data, AI, engineering, and product.

Examples for an AI course following the textbook Artificial Intelligence: A Modern Approach by Russell and Norvig.

Companion Code for Deconstructing Large Language Models

🧮 A collection of resources to learn mathematics for machine learning

This is the notes of the way of machine learning study. You may find something useful in it.