內容簡介
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.
作者簡介
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.
精彩書評
"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 [平裝] 下載 mobi epub pdf txt 電子書 格式
Machine Learning: The Art and Science of Algorithms that Make Sense of Data [平裝] 下載 mobi pdf epub txt 電子書 格式 2024
評分
☆☆☆☆☆
老公的生日禮物,我一個IT盲對比瞭N多的目錄選擇瞭這兩本。書紙很好,內容完全不懂,希望對老公有幫助。
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機器學習指南,這本書我不知道怎麼瞭買瞭兩本,也沒時間看。
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特朗普10日上午結束瞭對中國的國事訪問,乘專機離開北京。
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☆☆☆☆☆
書不錯,還麼就開始看
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經常買。。。。。。。
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☆☆☆☆☆
書已收到,還沒來得及看,紙張不錯,最後幾頁還有彩色的插圖。
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☆☆☆☆☆
很火的一個方嚮 顯然它不是很入門的一本書
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側漏MOTO哦吼歐諾哦咯通透性哦吼聽語音子虛烏有嗚嗚嗚嗚嗚嗚嗚
評分
☆☆☆☆☆
好的吧,從入門到退學。可立剋加進來。
Machine Learning: The Art and Science of Algorithms that Make Sense of Data [平裝] mobi epub pdf txt 電子書 格式下載 2024