Boschetti Alberto - Python data science essentials : become an efficient data science practitioner
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Copyright 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, 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: April 2015
Production reference: 1240415
Published by Packt Publishing Ltd.
Livery Place
35 Livery Street
Birmingham B3 2PB, UK.
ISBN 978-1-78528-042-9
www.packtpub.com
Authors
Alberto Boschetti
Luca Massaron
Reviewers
Robert Dempsey
Daniel Frimer
Kevin Markham
Alberto Gonzalez Paje
Bastiaan Sjardin
Michele Usuelli
Zacharias Voulgaris, PhD
Commissioning Editor
Julian Ursell
Acquisition Editor
Subho Gupta
Content Development Editor
Merwyn D'souza
Technical Editor
Namrata Patil
Copy Editor
Vedangi Narvekar
Project Coordinator
Neha Bhatnagar
Proofreaders
Simran Bhogal
Faye Coulman
Safis Editing
Dan McMahon
Indexer
Priya Sane
Production Coordinator
Komal Ramchandani
Cover Work
Komal Ramchandani
Alberto Boschetti is a data scientist with expertise in signal processing and statistics. He holds a PhD in telecommunication engineering and currently lives and works in London. In his work projects, he faces challenges involving natural language processing (NLP), machine learning, and probabilistic graph models everyday. He is very passionate about his job and he always tries to stay updated on the latest developments in data science technologies by attending meetups, conferences, and other events.
I would like to thank my family, my friends, and my colleagues. Also, a big thanks to the open source community.
Luca Massaron is a data scientist and marketing research director who specializes in multivariate statistical analysis, machine learning, and customer insight, with over a decade of experience in solving real-world problems and generating value for stakeholders by applying reasoning, statistics, data mining, and algorithms. From being a pioneer of web audience analysis in Italy to achieving the rank of a top 10 Kaggler, he has always been passionate about everything regarding data and analysis and about demonstrating the potentiality of data-driven knowledge discovery to both experts and nonexperts. Favoring simplicity over unnecessary sophistication, he believes that a lot can be achieved in data science by understanding its essentials.
To Yukiko and Amelia, for their loving patience. "Roads go ever ever on, under cloud and under star, yet feet that wandering have gone turn at last to home afar".
Robert Dempsey is an experienced leader and technology professional specializing in delivering solutions and products to solve tough business challenges. His experience in forming and leading agile teams, combined with more than 14 years of experience in the field of technology, enables him to solve complex problems while always keeping the bottom line in mind.
Robert has founded and built three start-ups in technology and marketing, developed and sold two online applications, consulted Fortune 500 and Inc. 500 companies, and spoken nationally and internationally on software development and agile project management.
He is currently the head of data operations at ARPC, an econometrics firm based in Washington, DC. In addition, he's the founder of Data Wranglers DC, a group dedicated to improving the craft of data wrangling, as well as a board member of Data Community DC.
In addition to spending time with his growing family, Robert geeks out on Raspberry Pis and Arduinos and automates most of his life with the help of hardware and software.
Daniel Frimer has been an advocate for the Python language for 2 years now. With a degree in applied and computational math sciences from the University of Washington, he has spearheaded various automation projects in the Python language involving natural language processing, data munging, and web scraping. In his side projects, he has dived into a deep analysis of NFL and NBA player statistics for his fantasy sports teams.
Daniel has recently started working in SaaS at a private company for online health insurance shopping called Array Health, in support of day-to-day data analysis and the perfection of the integration between consumers, employers, and insurers. He has also worked with data-centric teams at Amazon, Starbucks, and Atlas International.
Kevin Markham is a computer engineer, a data science instructor for General Assembly in Washington, DC, and the cofounder of Causetown, an online cause marketing platform for small businesses. He is passionate about teaching data science and machine learning and enjoys both Python and R. He founded Data School (http://dataschool.io) in order to provide in-depth educational resources that are accessible to data science novices. He has an active YouTube channel (http://youtube.com/dataschool) and can also be found on Twitter (@justmarkham
).
Alberto Gonzalez Paje is an economist specializing in information management systems and data science. Educated in Spain and the Netherlands, he has developed an international career as a data analyst at companies such as Coca Cola, Accenture, Bestiario, and CartoDB. He focuses on business strategy, planning, control, and data analysis. He loves architecture, cartography, the Mediterranean way of life, and sports.
Bastiaan Sjardin is a data scientist and entrepreneur with a background in artificial intelligence, mathematics, and machine learning. He has an MSc degree in cognitive science and mathematical statistics at the University of Leiden. In the past 5 years, he has worked on a wide range of data science projects. He is a frequent Community TA with Coursera for the "Social Network analysis" course at the University of Michigan. His programming language of choice is R and Python. Currently, he is the cofounder of Quandbee (www.quandbee.com), a company specialized in machine learning applications.
Michele Usuelli is a data scientist living in London, specializing in R and Hadoop. He has an MSc in mathematical engineering and statistics, and he has worked in fast-paced, growing environments, such as a big data start-up in Milan, the new pricing and analytics division of a big publishing company, and a leading R-based company. He is the author of R Machine Learning Essentials
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