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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] 电子书 下载 mobi epub pdf txt

评分☆☆☆☆☆

做活动，买了一堆书，希望能有用

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相比起抵达中国之前连发两条推特难掩激动之情，特朗普在离开中国前也连发多条推特，为自己的中国之行划下圆满句号。更值得注意的是，他的推特封面又换了！

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时下很火的内容要赶紧学习了

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还没拆开呢，看起来很不错。

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所措。本书从算法和Python 语言实现的角度，帮助读者认识机器学习。

评分☆☆☆☆☆

展示所讨论的算法的使用原则。全书共分为7 章，详细讨论了预测模型的两类核心算法、预测模型的构建、惩罚线性回归和集成方法的具体应用和实现。

评分☆☆☆☆☆

不错不错，用着挺好，要喜欢的。。。

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很好，很方便，方便快捷得很，赞赞赞！！！！

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