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] 下载 mobi epub pdf txt 电子书 格式
Machine Learning: The Art and Science of Algorithms that Make Sense of Data [平装] 下载 mobi pdf epub txt 电子书 格式 2025
评分
☆☆☆☆☆
这本书非常的好,直截了当的几个实践项目,由浅入深,特别适合想要直接上手的同学
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☆☆☆☆☆
质量一如既往的的好,快递速度一如既往的給力。
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☆☆☆☆☆
这本书非常的好,直截了当的几个实践项目,由浅入深,特别适合想要直接上手的同学
评分
☆☆☆☆☆
本书主要针对想提高机器学习技能的Python 开发人员,帮助他们解决某一特定的项
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☆☆☆☆☆
好好学习天天向上的人啊
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☆☆☆☆☆
内容且不说,就看印刷。你值得买吗?反正拿到后满满的失望。使用的代码示例根本看不清楚。这是用苹果手机拍的,它已经进行了锐化处理,看起来比原来还要清楚多了。
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☆☆☆☆☆
随着机器学习和人工智能技术的到来,Python现在火了起来。非常好的书,图书日,清空了好多书。
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☆☆☆☆☆
商品很不错,下次还会买,会向大家推荐购买
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Machine Learning: The Art and Science of Algorithms that Make Sense of Data [平装] mobi epub pdf txt 电子书 格式下载 2025