Topic: Machine Learning-related book recommendation

Topic: Machine Learning-related book recommendation

1.Programming collective intelligence,In recent years, getting started with a good book is the most important part to cultivate interest. On the top of the page, it is easy to be scared: P 2. Peter norvig'sAI, modern approach 2nd(Classic in a non-controversial domain ). 3.The elements of statistical learning,Strong mathematics. You can refer to this document. 4.Foundations of statistical Natural Language ProcessingIs recognized as a classic in the natural language processing field. 5.Data mining, concepts and techniquesThe books written by Chinese scientists are quite simple. 6.Managing gigabytes, A good book for information retrieval. 7.Information Theory: inference and Learning AlgorithmsFor more information, see. Related mathematical BASICS (reference books are not suitable for general reading ): 1. Linear Algebra: This reference book will not be listed. 2. Matrix mathematics:Matrix Analysis, Roger horn. Classic in the field of matrix analysis. 3. Probability Theory and statistics: William felle, probability theory and its application. It is also an excellent book. It can taste too heavy in mathematics and is not suitable for machine learning. SoDu leiRecommended by studentsAll of statisticsAnd said: Statistics are equally important in machine learning. We recommend all of statistics. This is a concise textbook of CMU. It focuses on concepts, simplifies computing, and simplifies concepts and statistical content unrelated to machine learning. It can be said that it is a good Quick Start material. 4. optimization method:Nonlinear Programming, 2ndReference books for nonlinear planning.Convex OptimizationReference for convex optimization. There are also some books that can refer to the optimization method entries on Wikipedia. To thoroughly understand the technical details of machine learning methods, we often need optimization methods (such as SVM.