Subramanian - Python Data Science Cookbook
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- Book:Python Data Science Cookbook
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- Publisher:[distributor] Bertrams, [distributor] Ingram Book Company, Packt Publishing Limited
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- Year:2015
- City:Birmingham
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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 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: November 2015
Production reference: 1041115
Published by Packt Publishing Ltd.
Livery Place
35 Livery Street
Birmingham B3 2PB, UK.
ISBN 978-1-78439-640-4
www.packtpub.com
Author
Gopi Subramanian
Reviewer
Bastiaan Sjardin
Commissioning Editor
Akram Hussain
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Cover Work
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Gopi Subramanian is a data scientist with over 15 years of experience in the field of data mining and machine learning. During the past decade, he has designed, conceived, developed, and led data mining, text mining, natural language processing, information extraction and retrieval, and search systems for various domains and business verticals, including engineering infrastructure, consumer finance, healthcare, and materials. In the loyalty domain, he has conceived and built innovative consumer loyalty models and designed enterprise-wide systems for personalized promotions. He has filed over ten patent applications at the US and Indian patent office and has several publications to his credit. He currently lives and works in Bangaluru, India.
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 from 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 at Coursera in the social network analysis course from the University of Michigan and the practical machine learning course from Johns Hopkins University. His programming language of choice is R and Python. Currently, he is the cofounder of Quandbee (www.quandbee.com), a company specializing in machine learning applications.
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Today, we live in a world of connected things where tons of data is generated and it is humanly impossible to analyze all the incoming data and make decisions. Human decisions are increasingly replaced by decisions made by computers. Thanks to the field of data science. Data science has penetrated deeply in our connected world and there is a growing demand in the market for people who not only understand data science algorithms thoroughly, but are also capable of programming these algorithms. Data science is a field that is at the intersection of many fields, including data mining, machine learning, and statistics, to name a few. This puts an immense burden on all levels of data scientists; from the one who is aspiring to become a data scientist and those who are currently practitioners in this field. Treating these algorithms as a black box and using them in decision-making systems will lead to counterproductive results. With tons of algorithms and innumerable problems out there, it requires a good grasp of the underlying algorithms in order to choose the best one for any given problem.
Python as a programming language has evolved over the years and today, it is the number one choice for a data scientist. Its ability to act as a scripting language for quick prototype building and its sophisticated language constructs for full-fledged software development combined with its fantastic library support for numeric computations has led to its current popularity among data scientists and the general scientific programming community. Not just that, Python is also popular among web developers; thanks to frameworks such as Django and Flask.
This book has been carefully written to cater to the needs of a diverse range of data scientistsstarting from novice data scientists to experienced onesthrough carefully crafted recipes, which touch upon the different aspects of data science, including data exploration, data analysis and mining, machine learning, and large scale machine learning. Each chapter has been carefully crafted with recipes exploring these aspects. Sufficient math has been provided for the readers to understand the functioning of the algorithms in depth. Wherever necessary, enough references are provided for the curious readers. The recipes are written in such a way that they are easy to follow and understand.
This book brings the art of data science with power Python programming to the readers and helps them master the concepts of data science. Knowledge of Python is not mandatory to follow this book. Non-Python programmers can refer to the first chapter, which introduces the Python data structures and function programming concepts.
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