Pattern Recognition and Machine Learning 新书_图书内容介绍_剧情呢
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Pattern Recognition and Machine Learning读书介绍

类别 页数 译者 网友评分 年代 出版社
书籍 738页 9.5 2020 Springer
定价 出版日期 最近访问 访问指数
USD 94.95 2020-02-20 … 2021-10-03 … 4
主题/类型/题材/标签
机器学习,模式识别,人工智能,数据挖掘,计算机,计算机科学,MachineLearning,learning,
作者
Christopher Bishop      ISBN:9780387310732    原作名/别名:《》
内容和作者简介
Pattern Recognition and Machine Learning摘要

The dramatic growth in practical applications for machine learning over the last ten years has been accompanied by many important developments in the underlying algorithms and techniques. For example, Bayesian methods have grown from a specialist niche to become mainstream, while graphical models have emerged as a general framework for describing and applying probabilistic techniques. The practical applicability of Bayesian methods has been greatly enhanced by the development of a range of approximate inference algorithms such as variational Bayes and expectation propagation, while new models based on kernels have had a significant impact on both algorithms and applications.

This completely new textbook reflects these recent developments while providing a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first-year PhD students, as well as researchers and practitioners. No previous knowledge of pattern recognition or machine learning concepts is assumed. Familiarity with multivariate calculus and basic linear algebra is required, and some experience in the use of probabilities would be helpful though not essential as the book includes a self-contained introduction to basic probability theory.

The book is suitable for courses on machine learning, statistics, computer science, signal processing, computer vision, data mining, and bioinformatics. Extensive support is provided for course instructors, including more than 400 exercises, graded according to difficulty. Example solutions for a subset of the exercises are available from the book web site, while solutions for the remainder can be obtained by instructors from the publisher. The book is supported by a great deal of additional material, and the reader is encouraged to visit the book web site for the latest information.

作者简介

Christopher M. Bishop is Deputy Director of Microsoft Research Cambridge, and holds a Chair in Computer Science at the University of Edinburgh. He is a Fellow of Darwin College Cambridge, a Fellow of the Royal Academy of Engineering, and a Fellow of the Royal Society of Edinburgh. His previous textbook "Neural Networks for Pattern Recognition" has been widely adopted.

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