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Harness the power of Python to analyze data and create insightful predictive models
earning Data Mining with Python Copyright C 2015 Packt Publishing All rights reserved. No part of this book may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, without the prior written permission of the publisher, except in the case of brief quotations embedded in critical articles or reviews Every effort has been made in the preparation of this book to ensure the accuracy of the information presented. However, the information contained in this book is sold without warranty cither express or implied. Neither the author, nor Packt Publishing and its dealers and distributors will be held liable for any damages caused or alleged to be caused directly or indirectly by this book Packt Publishing has endeavored to provide trademark information about all of the companies and products mentioned in this book by the appropriate use of capitals However, Packt Publishing cannot guarantee the accuracy of this information First published July 2015 Production reference: 1230715 Published by Packt Publishing Ltd Livery place 35 Livery street Birmingham b3 2PB, UK ISBN978-178439-605-3 www.packtpub.com Credits Author Project Coordinator Robert layton Nidhi joshi Reviewers Proofreader Asad ahamad Safis editing P Ashwin Christophe Van gysel Indexer Edward C. Delaporte∨ Priya Sane Commissioning Editor Graphi Sheetal aute Taron pereira Acquisition Editor Production coordinator James jones nt Development Edito Cover Work Nitesh Thakur Siddhesh saly Technical editor Naveenkumar jain Copy Editors Roshni Banerjee Trishya hajar about the author Robert layton has a phd in computer science and has been an avid Python programmer for many years. He has worked closely with some of the largest companies in the world on data mining applications for real-world data and has also been published extensively in international journals and conferences. Hle has extensive experience in cybercrime and text-based data analytics with a focus on behavioral modeling, authorship analysis, and automated open source intelligence. He has contributed code to a number of open source libraries including the scikit-learn library used in this book, and was a Google summer of Code mentor in 2014. Robert runs a data mining consultancy company called dataPipeline, providing data mining and analytics solutions to businesses in a variety of industries. about the reviewers asad ahamad is a data enthusiast and loves to work on data to solve challenging problems He did his master's degree in industrial mathematics with computer application at Jamia Millia Islamia, New Delhi. He admires mathematics a lot and always tries to use it to gain maximum profit for businesses He has good experience working in data mining, machine learning, and data science and has worked for various multinationals in india. he mainly uses r and Python to perform data wrangling and modeling. I Ie is fond of using open source tools for data analysis He is an active social media user. Feel free to connect with him on twitter at @asadtaj88. P Ashwin is a Bangalore-based engineer who wears many different hats depending on the occasion He graduated from IIIT, Hyderabad at in 2012 with an M Tech in computer science and engineering He has a total of 5 years of experience in the software industry where he has worked in different domains such as testing, data warehousing, replication, and automation. He is very well versed in DB concepts, SQL, and scripting with Bash and Python. Hle has earned professional certifications in products from Oracle, iBm, Informatica, and Teradata he's also an ISTQB-ccrtified tester In his free time, he volunteers in different technical hackathons or social service activities. He was introduced to raspberry pi in one of the hackathons and hes been hooked on it ever since. He writes a lot of code in Python, C, C++, and Shell on his Raspberry Pi B+ cluster. He's currently working on creating his own Beowulf cluster of 64 Raspberry pi 2s Christophe van gysel is pursuing a doctorate degree in computer science at the University of Amsterdam under the supervision of maarten de rijke and marcel Worring. He has interned at google, where he worked on large-scale machine learning and automated speech recognition. During his internship in Facebooks security infrastructure team, he worked on information security and implemented measures against compression side-channel attacks. In the past, he was active as a security researcher. He discovered and reported security vulnerabilities in the web services of Google, Facebook, Dropbox, and PayPal, among others Edward C. Delaporte v leads a software development group at the University of Illinois, and he has contributed to the documentation of the Kivy framework. He is thankful to all those whose contributions to the open source community made his career possible, and he hopes this book helps continue to attract enthusiasts to software development Www. Packtpub. com Support files, eBooks, discount offers, and more For support files and downloads related to your book, please visit www.packtpubcom Did you know that Packt offers e Book versions of every book published, with PDF andepubfilesavailableYoucanupgradetotheebookversionatwww.packtpub com and as a print book customer, you are entitled to a discount on the e Book copy Get in touch with us at service@packtpub com for more details Atwww.Packtpub.com,youcanalsoreadacollectionoffreetechnicalarticles sign up for a range of free newsletters and receive exclusive discounts and offers on packt books and ebooks PACKTLIB https://www2.packtpub.com/books/subscription/packtlib Do you need instant solutions to your It questions? PacktLib is Packt's online digital book library. Here, you can search, access, and read Packt's entire library of books y subscribe Fully searchable across every book published by Packt Copy and paste, print, and bookmark content On demand and accessible via a web browser Free access for packt account holders Ifyouhaveanaccountwithpacktatwww.packtpubcomyoucanusethistoaccess PacktLib today and view g entirely free books simply use your login credentials for immediate Table of contents Preface Chapter 1: Getting Started with Data Mining Introducing data mining Using Python and the IPython Notebook Installing Python Installing iPython Installing scikit-learn A simple affinity analysis example What is affinity analysis? Product recommendations 12335677880 Loading the dataset with NumPy Implementing a simple ranking of rules Ranking to find the best rules 13 A simple classification example What is classification 16 oading and preparing the dataset 16 Implementing the OneR algorithm Testing the algorithm 20 Summary 23 Chapter 2: Classifying with scikit-learn Estimators 25 scikit-earn estimators 25 Nearest neighbors 26 Distance metrics 27 Loading the dataset 29 Moving towards a standard workflow 31 Running the algorithm 32 Setting parameters 33

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woodshappy 有用 谢谢了
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空灵竹 资源不错,就是英文的,赞一个
Ali 很好的书籍,感谢分享。
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