內容簡介
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.
作者簡介
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.
精彩書評
"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 [平裝] 下載 mobi epub pdf txt 電子書 格式
Machine Learning: The Art and Science of Algorithms that Make Sense of Data [平裝] 下載 mobi pdf epub txt 電子書 格式 2025
評分
☆☆☆☆☆
一方麵可以熟知基本的眾多算法,這是基礎中的基礎,同時對麵試也有極大的作用。
評分
☆☆☆☆☆
老公買的特彆愛學習,一直在京東上買書,多搞活動。
評分
☆☆☆☆☆
所措。本書從算法和Python 語言實現的角度,幫助讀者認識機器學習。
評分
☆☆☆☆☆
最近買瞭不少python的書,重點還是在於堅持使用,纔能提高自己
評分
☆☆☆☆☆
書的包裝是有透明袋,書的內容不錯,待學習,但是紙張有點粗糙。
評分
☆☆☆☆☆
老公買的 正在看 還挺不錯
評分
☆☆☆☆☆
機器學習指南,這本書我不知道怎麼瞭買瞭兩本,也沒時間看。
評分
☆☆☆☆☆
很滿意的購物,很好用,送貨快,京東質量有保障,是正品
評分
☆☆☆☆☆
比超市便宜值得購買購買方便快遞給力
Machine Learning: The Art and Science of Algorithms that Make Sense of Data [平裝] mobi epub pdf txt 電子書 格式下載 2025