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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☆☆☆☆☆

最近买了不少python的书，重点还是在于坚持使用，才能提高自己

评分☆☆☆☆☆

完美！当天收货！排版紧密，全部干货，等于普通一倍厚的书。模块化安排的内容即可以学习也可以参考用！Double thumbs up!

评分☆☆☆☆☆

本书内容挺好的，适合研究这个领域的读一读，京东服务很好

评分☆☆☆☆☆

都是跟风学这个吧，作为快速入门的书籍有点用，偏实践。想要机器学习的内涵讲解，这本书是远远不够的

评分☆☆☆☆☆

一次买了很多书，就是看京东送货快捷方便，以后会经常光顾的。

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打算入门人工智能的可以考虑看一下，需要一定的基础。

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东西不错

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书本质量很好。包装不太好，箱内无填充物，快递还要自取。

评分☆☆☆☆☆

写的很不错的书。

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