Books
Practical guides for business and technical professionals. Free to read online.
Data Science Handbook
A Complete Guide to Machine Learning, Optimization and AI — Mathematical Foundations & Practical Implementations
A comprehensive guide covering the mathematical foundations and practical implementations of machine learning, optimization, and artificial intelligence. From fundamental concepts to advanced techniques, this handbook provides both theoretical depth and real-world applications.
Key Topics
For
Data scientists, ML engineers, researchers, students, quants, math enthusiasts and anyone interested in the mathematical foundations of machine learning, optimization, and artificial intelligence.
Language AI Handbook
A Practitioner's Guide from Fundamentals to State-of-the-Art
A comprehensive guide from the fundamentals of natural language processing to cutting-edge large language models and the latest research breakthroughs. Learn about NLP, transformers, GPT, BERT, and modern language AI.
Key Topics
For
Engineers, researchers, students, AI enthusiasts, linguists, product managers, and anyone interested in understanding or building modern language AI systems, from foundational NLP to advanced large language models.
History of Language AI
How We Taught Machines to Read, Write, and Reason Through a Hundred Years of Discovery
A journey through the history of language AI, from the early days of information theory to modern large language models. Discover the key breakthroughs, influential figures, and technological advances that shaped how machines understand and generate human language.
Key Topics
For
Historians, researchers, students, AI enthusiasts, and anyone interested in understanding how language AI evolved from theoretical concepts to the transformative technology of today.
AI Agent Handbook
Understanding the Full Stack of Autonomous AI Agents—Models, Memory, Tools, Reasoning, Evaluation, and Operations
A comprehensive guide to building and deploying intelligent autonomous agents that can reason, act, and learn. Covers the full stack from foundational models to advanced reasoning techniques, memory systems, tool integration, evaluation methods, and operational best practices.
Key Topics
For
AI engineers, researchers, product managers, and anyone interested in building intelligent autonomous agents that can reason, plan, and act in complex environments.
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