Data Mining, Fourth Edition: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series pdf epub mobi txt 電子書 下載 2024


Data Mining, Fourth Edition: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series

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Ian H. Witten
Morgan Kaufmann
2016-12-9
654
USD 66.45
Paperback
9780128042915

圖書標籤: 編程  經典  統計學  機器學習  機器學習  新西蘭  數據挖掘  數學   


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发表于2024-11-12

Data Mining, Fourth Edition: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series epub 下載 mobi 下載 pdf 下載 txt 電子書 下載 2024

Data Mining, Fourth Edition: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series epub 下載 mobi 下載 pdf 下載 txt 電子書 下載 2024

Data Mining, Fourth Edition: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series pdf epub mobi txt 電子書 下載 2024



圖書描述

Data Mining: Practical Machine Learning Tools and Techniques, Fourth Edition, offers a thorough grounding in machine learning concepts, along with practical advice on applying these tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning teaches readers everything they need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches.

Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Authors Witten, Frank, Hall, and Pal include today's techniques coupled with the methods at the leading edge of contemporary research.

Provides a thorough grounding in machine learning concepts, as well as practical advice on applying the tools and techniques to data mining projectsPresents concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methodsIncludes a downloadable WEKA software toolkit, a comprehensive collection of machine learning algorithms for data mining tasks-in an easy-to-use interactive interfaceIncludes open-access online courses that introduce practical applications of the material in the book

Data Mining, Fourth Edition: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series 下載 mobi epub pdf txt 電子書

著者簡介

From the Back Cover

Data Mining: Practical Machine Learning Tools and Techniques offers a thorough grounding in machine learning concepts as well as practical advice on applying the tools and techniques in real-world data mining situations. This highly anticipated fourth edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know to get going, from preparing inputs, interpreting outputs, evaluating results, to the algorithmic methods at the heart of successful data mining approaches. Extensive updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including substantial new chapters on probabilistic methods and on deep learning. Accompanying the book is a new version of the popular WEKA machine learning software from the University of Waikato. Witten, Frank, Hall and Pal include the techniques of today as well as methods at the leading edge of contemporary research. Key Features Include: Provides a thorough grounding in machine learning concepts as well as practical advice on applying the tools and techniques to your data mining projects Concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods Downloadable WEKA software toolkit, a comprehensive collection of machine learning algorithms for data mining tasks-in an easy-to-use interactive interface. Accompanying open-access online courses that introduce practical application of the material in the book.

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About the Author

Ian H. Witten is a professor of computer science at the University of Waikato in New Zealand. He directs the New Zealand Digital Library research project. His research interests include information retrieval, machine learning, text compression, and programming by demonstration. He received an MA in Mathematics from Cambridge University, England; an MSc in Computer Science from the University of Calgary, Canada; and a PhD in Electrical Engineering from Essex University, England. He is a fellow of the ACM and of the Royal Society of New Zealand. He has published widely on digital libraries, machine learning, text compression, hypertext, speech synthesis and signal processing, and computer typography. He has written several books, the latest being Managing Gigabytes (1999) and Data Mining (2000), both from Morgan Kaufmann.Eibe Frank lives in New Zealand with his Samoan spouse and two lovely boys, but originally hails from Germany, where he received his first degree in computer science from the University of Karlsruhe. He moved to New Zealand to pursue his Ph.D. in machine learning under the supervision of Ian H. Witten, and joined the Department of Computer Science at the University of Waikato as a lecturer on completion of his studies. He is now an associate professor at the same institution. As an early adopter of the Java programming language, he laid the groundwork for the Weka software described in this book. He has contributed a number of publications on machine learning and data mining to the literature and has refereed for many conferences and journals in these areas.>Mark A. Hall holds a bachelor’s degree in computing and mathematical sciences and a Ph.D. in computer science, both from the University of Waikato. Throughout his time at Waikato, as a student and lecturer in computer science and more recently as a software developer and data mining consultant for Pentaho, an open-source business intelligence software company, Mark has been a core contributor to the Weka software described in this book. He has published a number of articles on machine learning and data mining and has refereed for conferences and journals in these areas.

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圖書目錄


Data Mining, Fourth Edition: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series pdf epub mobi txt 電子書 下載
想要找書就要到 小哈圖書下載中心
立刻按 ctrl+D收藏本頁
你會得到大驚喜!!

用戶評價

評分

WEKA篇幅終於減少瞭

評分

WEKA篇幅終於減少瞭

評分

WEKA篇幅終於減少瞭

評分

WEKA篇幅終於減少瞭

評分

WEKA篇幅終於減少瞭

讀後感

評分

这本书确实如所知道的那样,翻译得很水。很多一些概念的东西就像把你隔在某种屏障外,然后其实说的并不是那么枯燥的东西………… 本书主要还是介绍机器学习的,用这本书的目的就是为了了解weka中算法实现的思想。从这点出发这本书还算是比较值当的了,比官方的文档确实还是要精...  

評分

評分

断断续续做了8年股市,从爬数据,到做数据挖掘框架,趴了好多书。 一晃8年,从20多岁的青葱年代到不敢多念想的奔四岁月。 时间从挥霍到点滴的珍惜,不知道还能坚持多久。 最近结合weka搭建一个自适应的机器学习引擎。 希望能有所突破。自己选择没有后悔, 只有孤注一掷的往...  

評分

一会是查询偏差,一会是搜索偏差~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~  

評分

这本书确实如所知道的那样,翻译得很水。很多一些概念的东西就像把你隔在某种屏障外,然后其实说的并不是那么枯燥的东西………… 本书主要还是介绍机器学习的,用这本书的目的就是为了了解weka中算法实现的思想。从这点出发这本书还算是比较值当的了,比官方的文档确实还是要精...  

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Data Mining, Fourth Edition: Practical Machine Learning Tools and Techniques (Morgan Kaufmann Series pdf epub mobi txt 電子書 下載 2024


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