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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

評分☆☆☆☆☆

滿600-400麼，囤貨的最佳時期，好好學習，天天嚮上

評分☆☆☆☆☆

書很好，果凍買的，便宜，講解很細，沒看完。快遞包裝很結實，沒任何問題。京東物流飛快，服務超好。

評分☆☆☆☆☆

說的包裝很完整，隻是還沒有打開看，應該還不錯吧，這個係列的書買瞭很多

評分☆☆☆☆☆

此用戶未填寫評價內容

評分☆☆☆☆☆

書很好，內容豐富，值得學習，需要好好看書瞭哈哈哈哈?

評分☆☆☆☆☆

書寫的不錯，是正版，適閤大數據和生物信息學的人學習，京東速度很快，支持

評分☆☆☆☆☆

正版書籍，質量不錯。單位采購買瞭不少外文書，都很貴，還沒來得及看

評分☆☆☆☆☆

好的吧，從入門到退學。可立剋加進來。

評分☆☆☆☆☆

不錯，是該好好學習瞭

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