This book provides a comprehensive foundation of machine learning. To answer the questions of what to learn, how to learn, what to get from learning, and how to evaluate,as well as what is meant by learning, the book focuses on the fundamental basics of machine learning, its methodology, theory, algorithms, and evaluations, together with some philosophical thinking on comparison between machine learning and human learning for machinery intelligence.The book is organized as follows:Introduction (Chapter 1), Evaluation (Chapter 2),Supervised learning (Chapters 3, 4, and 5), Unsupervised learning (Chapter 6),Representation learning (Chapter 7), Problem decomposition (Chapter 8), Ensemble learn

《机器学习的综合基础》目录参见目录图