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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

評分☆☆☆☆☆

商品包裝有待進一步加強。

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本書專注於兩類核心的“算法族”，即懲罰綫性迴歸和集成方法，並通過代碼實例來

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☆☆☆☆☆

書已收到，還沒來得及看，紙張不錯，最後幾頁還有彩色的插圖。

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搞活動事時買的，非常的劃算。。。産品質量很不錯。。！

評分☆☆☆☆☆

不厚，原價將近七十。一年不到印瞭十次，三八節半價優惠，多快好省！

評分☆☆☆☆☆

內容且不說，就看印刷。你值得買嗎？反正拿到後滿滿的失望。使用的代碼示例根本看不清楚。這是用蘋果手機拍的，它已經進行瞭銳化處理，看起來比原來還要清楚多瞭。

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正版書籍，質量不錯。單位采購買瞭不少外文書，都很貴，還沒來得及看

評分☆☆☆☆☆

這本書非常好非常基礎，順便把大學數學重新學瞭一遍。

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