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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

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机器学习指南，这本书我不知道怎么了买了两本，也没时间看。

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书很好，果冻买的，便宜，讲解很细，没看完。快递包装很结实，没任何问题。京东物流飞快，服务超好。

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翻了一下，其实也没啥啊，不过多看看，吸收下经验也很好～～～活动半价，如果可以跟电子版一起附加就更好了～～～～

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正准备学习的机器学习算法与预测算法。正品书

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好，很好，非常好，好很好，非常好，非常好！！！！非常好非常好！非常好非常好！

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刚开始看，准备朝着这个方向发展

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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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这本书非常好非常基础，顺便把大学数学重新学了一遍。

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