内容简介
As one of the most comprehensive machine learning texts around, this book does justice to the field's incredible richness, but without losing sight of the unifying principles. Peter Flach's clear, example-based approach begins by discussing how a spam filter works, which gives an immediate introduction to machine learning in action, with a minimum of technical fuss. Flach provides case studies of increasing complexity and variety with well-chosen examples and illustrations throughout. He covers a wide range of logical, geometric and statistical models and state-of-the-art topics such as matrix factorisation and ROC analysis. Particular attention is paid to the central role played by features. The use of established terminology is balanced with the introduction of new and useful concepts, and summaries of relevant background material are provided with pointers for revision if necessary. These features ensure Machine Learning will set a new standard as an introductory textbook.
作者简介
Peter Flach has more than twenty years of experience in machine learning teaching and research. He is Editor-in-Chief of Machine Learning and Program Co-Chair of the 2009 ACM Conference on Knowledge Discovery and Data Mining and the 2012 European Conference on Machine Learning and Data Mining. His research spans all aspects of machine learning, from knowledge representation and the use of logic to learn from highly structured data to the analysis and evaluation of machine learning models and methods to large-scale data mining. He is particularly known for his innovative use of Receiver Operating Characteristic (ROC) analysis for understanding and improving machine learning methods. These innovations have proved their effectiveness in a number of invited talks and tutorials and now form the backbone of this book.
精彩书评
"This textbook is clearly written and well organized. Starting from the basics, the author skillfully guides the reader through his learning process by providing useful facts and insight into the behavior of several machine learning techniques, as well as the high-level pseudocode of many key algorithms."
——Fernando Berzal, Computing Reviews
前言/序言
Machine Learning: The Art and Science of Algorithms that Make Sense of Data [平装] 下载 mobi epub pdf txt 电子书 格式
Machine Learning: The Art and Science of Algorithms that Make Sense of Data [平装] 下载 mobi pdf epub txt 电子书 格式 2025
评分
☆☆☆☆☆
书很好,内容很不错,写得很详细
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☆☆☆☆☆
很好的一本书,物流相当快,不过没来得及看,618一百多买了四百左右的书,2333
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☆☆☆☆☆
很好,很方便,方便快捷得很,赞赞赞!!!!
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☆☆☆☆☆
好书,写的很详细,受益匪浅,以后还会买
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☆☆☆☆☆
不要堕落,保证物质品质,质量,坚持为人民服务才是王道。
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☆☆☆☆☆
喜欢这本书,刚评价,本人没做到实践,但书里给的机器学习实践感觉很好
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☆☆☆☆☆
屯书进行时!!!特别不错,正版图书!!!
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☆☆☆☆☆
花了近两个月的业余时间来看这本书。正像我说的那样,大约只读懂了我能读懂的部分。
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☆☆☆☆☆
希望里面有足够的算法分析和参考,可以拿来实现分析!
Machine Learning: The Art and Science of Algorithms that Make Sense of Data [平装] mobi epub pdf txt 电子书 格式下载 2025