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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☆☆☆☆☆

非常不错的书， 适合与时俱进， 拥抱新东西，活到老学到老的人。

评分☆☆☆☆☆

书还是不错的，有点泛，了解各方面应用不错，内容默认很多功能读者都会，所以初学者不建议用，建议至少学点Python的基础

评分☆☆☆☆☆

这本书非常好非常基础，顺便把大学数学重新学了一遍。

评分☆☆☆☆☆

个人感觉不错，Python的机器学习应该是未来的一个方向！

评分☆☆☆☆☆

京东物流高效 快递包装完整 购物体验非常好

评分☆☆☆☆☆

京东书很好，是正品，有一两本包装也开了，但是内容完整，没有缺烂，希望多搞活动，会一直关注。

评分☆☆☆☆☆

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☆☆☆☆☆

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。

评分☆☆☆☆☆

还好还好还好还好还好还好还好还好还好还好还好还好

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