Explore the core principles of artificial intelligence with ‘Foundations of Machine Learning, Second Edition’. This graduate-level textbook, from The MIT Press, offers a comprehensive introduction to machine learning, focusing on the analysis and theory of algorithms. Ideal for students and researchers, it covers essential modern topics, providing the theoretical basis and conceptual tools for understanding and justifying algorithms. Dive into key areas like PAC learning, generalization bounds, SVMs, kernel methods, boosting, and reinforcement learning. This updated edition introduces new chapters on model selection and entropy models, along with expanded appendixes on Fenchel duality and information theory. Enhance your understanding of AI with this insightful and thoroughly revised resource from The Bookish Owl.