Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict future data. This textbook offers a comprehensive and self-contained introduction to the field of machine learning, a unified, probabilistic approach. The coverage combines breadth and depth, offering necessary background material on such topics as probability, optimization, and linear algebra as well as discussion of recent developments in the field, including conditional random fields, L1 regularization, and deep learning. The book is written in an informal, accessible style, complete with pseudo-code for the most important algorithms. All topics are copiously illustrated with color images and worked examples drawn from such application domains as biology, text processing, computer vision, and robotics. Rather than providing a cookbook of different heuristic methods, the book stresses a principled model-based approach, often using the language of graphical models to specify models in a concise and intuitive way. Almost all the models described have been implemented in a MATLAB software package--PMTK (probabilistic modeling toolkit)--that is freely available online. The book is suitable for upper-level undergraduates with an introductory-level college math background and beginning graduate students.

《正则指引》针对作者在开发中遇到的实际问题，以及其他开发人员咨询的问题，总结出一套使用正则表达式解题的办法，并通过具体的例子指导读者拆解、分析问题。全书分为三大部分：第一部分主要讲解正则表达式的基础知识，涵盖了常见正则表达式中的各种功能和结构；第二部分主要讲解关于正则表达式的更深入的知识，详细探讨了编码问题、匹配原理、解题思路；第三部分将之前介绍的各种知识落实到6种常用语言.NET、Java、JavaScript、PHP、Python、Ruby中，不但详细介绍了语言中正则表达式的用法，更点明了版本之间的细微差异，既可以作为专门学习的教材，也可以作为有用的参考手册。 本书适合经常需要进行文本处理（比如日志分析或网络运维）的技术人员、熟悉常用开发语言的程序员，以及已经对正则表达式有一定了解的读者阅读。

For one or two-semester, undergraduate or graduate-level courses in Artificial Intelligence. The long-anticipated revision of this best-selling text offers the most comprehensive, up-to-date introduction to the theory and practice of artificial intelligence. Click on "Features" tab below for more information Resources: Visit the author's website http://aima.cs.berkeley.edu/ to access both student and instructor resources including Power Point slides, syllabus. homework and exams, and solutions text problems.

编辑推荐：人工智能哲学是伴随现代信息理论和计算机技术发展起来的一个哲学分支。本书收集了人工智能研究领域著名学者的十五篇代表性论文，这些论文为计算机科学的发展和人工智能哲学的建立作出了开创性的贡献。这些文章总结了人工智能发展的历程，近年来该学科发展的趋势，以及人工智能中的重要课题。在这些划时代的著作中，包括有：现代计算机理论之父艾伦·图灵的“计算机与智能”；著名美国哲学家塞尔的“心灵，大脑与程序”；

集智俱乐部是一个从事学术研究、享受科学乐趣的探索者组成的团体，倡导以平等开放的态度、科学实证的精神进行跨学科的研究与交流，力图搭建一个中国的“没有围墙的研究所”。这些令人崇敬的、充满激情与梦想的集智俱乐部成员将带你了解图灵机模型、冯•诺依曼计算机体系结构、怪圈与哥德尔定理、通用人工智能、深度学习、人类计算与自然语言处理，与你一起展开一场令人热血沸腾的科学之旅。