Bayesian Reasoning and Machine Learning

贝叶斯推理和机器学习

基本信息

Author：David Barber

Format：Hardback | 735 pages

Dimensions：193 x 251 x 37mm | 1,710g

Publication date：01 Apr 2012

Publisher：Cambridge University Press

Language: English

ISBN10：0521518148

ISBN13：9780521518147

页面参数仅供参考，具体以实物为准

内容简介

机器学习方法以有限的资源快速地从大量数据集中提取价值。它们是广泛应用于工业领域的工具，包括搜索引擎、DNA测序、股票市场分析和机器人移动，而且它们的使用正在迅速普及。知道这些方法的人可以选择有回报的工作。这个动手操作的文本打开这些机会计算机科学学生适度的数学背景。它是专为在线性代数和微积分方面有一定背景的大四本科生和硕士学生设计的。本书全面连贯，易于理解，它在图形模型框架内开发从基本推理到高级技术的一切。学生们学到的不仅仅是一套技巧，他们还培养了分析问题和解决问题的能力，使他们能够适应现实世界。无数的例子和练习，都基于计算机和理论，包括在每一章。为学生和教师提供的资源，包括MATLAB工具箱，可以在网上找到。

Machine learning methods extract value from vast data sets quickly and with modest resources. They are established tools in a wide range of industrial applications, including search engines, DNA sequencing, stock market analysis, and robot locomotion, and their use is spreading rapidly. People who know the methods have their choice of rewarding jobs. This hands-on text opens these opportunities to computer science students with modest mathematical backgrounds. It is designed for final-year undergraduates and master's students with limited background in linear algebra and calculus. Comprehensive and coherent, it develops everything from basic reasoning to advanced techniques within the framework of graphical models. Students learn more than a menu of techniques, they develop analytical and problem-solving skills that equip them for the real world. Numerous examples and exercises, both computer based and theoretical, are included in every chapter. Resources for students and instructors, including a MATLAB toolbox, are available online.