易水涵的专栏

Ethem ALPAYDIN The MIT Press The goal of machine learning is to program computers to use example data or past experience to solve a given problem. Many successful applications of machine learning exist already, including systems that analyze past sales data to predict customer behavior, optimize robot behavior so that a task can be completed using minimum resources, and extract knowledge from bioinformatics data. Introduction to Machine Learning is a comprehensive textbook on the subject, covering a broad array of topics not usually included in introductory machine learning texts. In order to present a unified treatment of machine learning problems and solutions, it discusses many methods from different fields, including statistics, pattern recognition, neural networks, artificial intelligence, signal processing, control, and data mining. All learning algorithms are explained so that the student can easily move from the equations in the book to a computer program. The text covers such topics as supervised learning, Bayesian decision theory, parametric methods, multivariate methods, multilayer perceptrons, local models, hidden Markov models, assessing and comparing classification algorithms, and reinforcement learning. New to the second edition are chapters on kernel machines, graphical models, and Bayesian estimation; expanded coverage of statistical tests in a chapter on design and analysis of machine learning experiments; case studies available on the Web (with downloadable results for instructors); and many additional exercises. All chapters have been revised and updated.

作者: Henrik Brink / Joseph Richards / Mark Fetherolf 出版社: Manning Publications 出版年: 2015-12-31 页数: 400 Every entry-level Data Scientist should read this book before he/she officially start working in the industry. 整个用机器学习做一个实际问题的流程基本都有了，有代码和模型。

protege的中文指导手册，很实用的教程，对学习语义很有帮助。

Hibernate in action 第二版 学习Hibernate，进行SSH开发的工具书。

SpringGuide,经典的Spring教程。 学习Spring的必备工具书。

Flex起步指导书籍，版本为Flex 3。是学习Flex技术不错的电子书籍。

关于Struts 2的详细描述，是开发使用Struts 2不可多得的资料