Learning scikit-learn Machine Learning in Python(PACKT,2013)

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Machine learning, the art of creating applications that learn from experience and data, has been around for many years. However, in the era of “big data”, huge amounts of information is being generated. This makes machine learning an unavoidable source of new data-based approximations for problem solving. With Learning scikit-learn: Machine Learning in Python, you will learn to incorporate machine learning in your applications. The book combines an introduction to some of the main concepts and methods in machine learning with practical, hands-on examples of real-world problems. Ranging from handwritten digit recognition to document classification, examples are solved step by step using Scikit-learn and Python. The book starts with a brief introduction to the core concepts of machine learning with a simple example. Then, using real-world applications and advanced features, it takes a deep dive into the various machine learning techniques. You will learn to evaluate your results and apply advanced techniques for preprocessing data. You will also be able to select the best set of features and the best methods for each problem. With Learning scikit-learn: Machine Learning in Python you will learn how to use the Python programming language and the scikit-learn library to build applications that learn from experience, applying the main concepts and techniques of machine learning.
Learning scikit-learn Machine Learning in Python Copyright o 2013 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, either express or implied. Neither the authors, 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: November 2013 Production reference: 1181113 Published by Packt Publishing Ltd Livery place 35 Livery street Birmingham B3 2PB,UK ISBN978-1-78328-193-0 www.packtpub.com CoverImagebyFaizFattohi(faizfattohi@gmail.com) Credits Authors Project Coordinator Raul garreta Aboli ambardekar Guillermo moncecchi Proofreader Reviewers Katherine Tarr Andreas Hjortgaard danielsen Noel dawe Indexer Monica Ajmera Mehta Gavin Hackling Acquisition Editors Graphics Abhinash sahu Kunal parikh Owen roberts Production Co-ordinator Pooja chiplunkar Commissioning editor Deepika Sing Cover work Pooja Chiplunkar Technical editors Shashank desai Iram malik Copy Editors Sarang Chari Janbal dharmaraj Aditya nair About the authors Raul garreta is a Computer Engineer with much experience in the theory and application of Artificial Intelligence(AD), where he specialized in Machine Learning and Natural Language Processing(NLP) He has an entrepreneur profile with much interest in the application of science, technology, and innovation to the Internet industry and startups. He has worked in many software companies, handling everything from video games to implantable medical devices In 2009, he co-founded Tryolabs with the objective to apply ai to the development of intelligent software products, where he performs as the Cto and Product Manager of the company. Besides the application of Machine Learning and NLP, Tryolabs expertise lies in the Python programming language and has been catering to many clients in Silicon valley. Raul has also worked in the development of the python community in Uruguay, co-organizing local PyDay and Py Con conferences He is also an assistant professor at the computer Science Institute of Universidad de a republica in Uruguay since 2007, where he has been working on the courses of Machine Learning nlp, as well as Automata Theory and Formal Languages. Besides this, he is finishing his Masters degree in Machine Learning and NLP Hle is also very interested in the research and application of robotics, Quantum Computing, and Cognitive Modeling. Not only is he a technology enthusiast and science fiction lover (geek) but also a big fan of arts, such as cinema, photography, and painting I would like to thank my girlfriend for putting up with my long working sessions and always supporting me. Thanks to my parents grandma, and aunt Pinky for their unconditional love and for always supporting my projects. Thanks to my friends and teammates at Tryolabs for always pushing me forward. Thanks Guillermo for joining me in writing this book. Thanks Diego Garat for introducing me to the amazing world of machine Learning back in 2005 Also, i would like to have a special mention to the open source Python and scikit-learn community for their dedication and professionalism in developing these beautiful tools Guillermo moncecchi is a Natural Language Processing researcher at the Universidad de la republica of Uruguay. He received a Phd in Informatics from the Universidad de la republica, Uruguay and a Ph. D in Language Sciences from the Universite Paris Ouest, France. He has participated in several international projects on NLP. He has almost 15 years of teaching experience on Automata Theory, Natural Language Processing, and Machine Learning He also works as head developer at the montevideo council and has lead the development of several public services for the council, particularly in the Geographical Information Systems area. He is one of the Montevideo Open Data movement leaders, promoting the publication and exploitation of the citys data I would like to thank my wife and kids for putting up with my late night writing sessions and my family for being there you are the best i have Thanks to Javier Couto for his invaluable advice. Thanks to Raul for inviting me to write this book. Thanks to all the people of the Natural language group and the instituto de computation at the Universidad de la republica. I am proud of the great job we do every day building the uruguayan NLP and ml community About the reviewers Andreas Hjortgaard Danielsen holds a Master's degree in Computer Science from the University of Copenhagen, where he specialized in Machine Learning and computer vision While writing his master's thesis, he was an intern research student in the Lampert group at the Institute of Science and Technology (IST), Austria in Vienna. The topic of his thesis was object localization using conditional random fields with special focus on efficient parameter learning He now works as a software developer in the information services industry where he has used scikit-learn for topic classification of text documents. See more on his websiteathttp://www.hjortgaard.net/. Noel Dawe is a Ph D student in the field of Experimental High Energy Particle physics at Simon Fraser University, Canada. As a member of the atlas collaboration, he has been a part of the search team for the Higgs boson using high energy proton-proton collisions at CERNs Large Hadron Collider(LHc)in Geneva, Switzerland. In his free time, he enjoys contributing to open source scientific software, including scikit-learn He has developed a significant interest toward Machine learning, to the benefit of his research where he has employed many of the concepts and techniques introduced in this book to improve the identification of tau leptons in the atlas detector and later to extract the small signature of the i liggs boson from the vast amount of LHC collision data. He continues to learn and apply new data analysis techniques, some seen as unconventional in his field, to solve the problems of increasing complexity and growing data sets Gavin Hackeling is a Developer and Creative Technologist based in New York City. He is a graduate from New York University in Interactive Telecommunications P rogram Www.Packtpub.com Support files, eBooks, discount offers and more Youmightwanttovisitwww.PacktPub.comforsupportfilesanddownloadsrelated to your book 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 serviceapacktpub com for more details Atwww.packtpub.comyoucanalsoreadacollectionoffreetechnicalarticlessign up for a range of free newsletters and receive exclusive discounts and offers on Packt books and ebooks HUPACKTLiB http://packtlib.Packtpub.com Do you need instant solutions to your It questions? PacktLib is Packt's online digital book library. Here, you can access, read and search across Packt's entire library of books hy Subscribe? Fully searchable across every book published by packt Copy and paste, print and bookmark content On demand and accessible via web browser Free Access for packt account holders IfyouhaveanaccountwithPacktatwww.packtPubcomyoucanusethistoaccess PacktLib today and view nine entirely free books Simply use your login credentials for immediate access Table of contents Preface Chapter 1: Machine Learning-A Gentle Introduction Installing scikit-learn Linux Mac Windows 567888 Checking your installation Our first machine learning method-linear classification 10 Evaluating our results Machine learning categories 20 Important concepts related to machine learning Summary 23 Chapter 2: Supervised Learning 25 Image recognition with Support Vector Machines 25 Training a Support Vector Machine 28 Text classification with naive bayes 33 Preprocessing the data 35 Training a naive bayes classifier 36 Evaluating the performance 40 Explaining Titanic hypothesis with decision trees 41 Preprocessing the data 43 Training a decision tree classifier 47 Interpreting the decision tree 49 Random forests- randomizing decisions 51 Evaluating the performance 52

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