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Shukla - Haskell data analysis cookbook: explore intuitive data analysis techniques and powerful machine learning methods using over 130 practical recipes

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Shukla Haskell data analysis cookbook: explore intuitive data analysis techniques and powerful machine learning methods using over 130 practical recipes
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Haskell Data Analysis Cookbook

Haskell Data Analysis Cookbook

Copyright 2014 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: June 2014

Production reference: 1180614

Published by Packt Publishing Ltd.

Livery Place

35 Livery Street

Birmingham B3 2PB, UK.

ISBN 978-1-78328-633-1

www.packtpub.com

Cover image by Jarek Blaminsky (<>)

Credits

Author

Nishant Shukla

Reviewers

Lorenzo Bolla

James Church

Andreas Hammar

Marisa Reddy

Commissioning Editor

Akram Hussain

Acquisition Editor

Sam Wood

Content Development Editor

Shaon Basu

Technical Editors

Shruti Rawool

Nachiket Vartak

Copy Editors

Sarang Chari

Janbal Dharmaraj

Gladson Monteiro

Deepa Nambiar

Karuna Narayanan

Alfida Paiva

Project Coordinator

Mary Alex

Proofreaders

Paul Hindle

Jonathan Todd

Bernadette Watkins

Indexer

Hemangini Bari

Graphics

Sheetal Aute

Ronak Dhruv

Valentina Dsilva

Disha Haria

Production Coordinator

Arvindkumar Gupta

Cover Work

Arvindkumar Gupta

About the Author

Nishant Shukla is a computer scientist with a passion for mathematics. Throughout the years, he has worked for a handful of start-ups and large corporations including WillowTree Apps, Microsoft, Facebook, and Foursquare.

Stepping into the world of Haskell was his excuse for better understanding Category Theory at first, but eventually, he found himself immersed in the language. His semester-long introductory Haskell course in the engineering school at the University of Virginia (http://shuklan.com/haskell) has been accessed by individuals from over 154 countries around the world, gathering over 45,000 unique visitors.

Besides Haskell, he is a proponent of decentralized Internet and open source software. His academic research in the fields of Machine Learning, Neural Networks, and Computer Vision aim to supply a fundamental contribution to the world of computing.

Between discussing primes, paradoxes, and palindromes, it is my delight to invent the future with Marisa.

With appreciation beyond expression, but an expression nonethelessthank you Mom (Suman), Dad (Umesh), and Natasha.

About the Reviewers

Lorenzo Bolla holds a PhD in Numerical Methods and works as a software engineer in London. His interests span from functional languages to high-performance computing to web applications. When he's not coding, he is either playing piano or basketball.

James Church completed his PhD in Engineering Science with a focus on computational geometry at the University of Mississippi in 2014 under the advice of Dr. Yixin Chen. While a graduate student at the University of Mississippi, he taught a number of courses for the Computer and Information Science's undergraduates, including a popular class on data analysis techniques. Following his graduation, he joined the faculty of the University of West Georgia's Department of Computer Science as an assistant professor. He is also a reviewer of The Manga Guide To Regression Analysis , written by Shin Takahashi , Iroha Inoue , and Trend-Pro Co. Ltd. , and published by No Starch Press .

I would like to thank Dr. Conrad Cunningham for recommending me to Packt Publishing as a reviewer.

Andreas Hammar is a Computer Science student at Norwegian University of Science and Technology and a Haskell enthusiast. He started programming when he was 12, and over the years, he has programmed in many different languages. Around five years ago, he discovered functional programming, and since 2011, he has contributed over 700 answers in the Haskell tag on Stack Overflow, making him one of the top Haskell contributors on the site. He is currently working part time as a web developer at the Student Society in Trondheim, Norway.

Marisa Reddy is pursuing her B.A. in Computer Science and Economics at the University of Virginia. Her primary interests lie in computer vision and financial modeling, two areas in which functional programming is rife with possibilities.

I congratulate Nishant Shukla for the tremendous job he did in writing this superb book of recipes and thank him for the opportunity to be a part of the process.

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The accompanying source code is also available at https://github.com/BinRoot/Haskell-Data-Analysis-Cookbook.

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Preface

Data analysis is something that many of us have done before, maybe even without knowing it. It is the essential art of gathering and examining pieces of information to suit a variety of purposesfrom visual inspection to machine learning techniques. Through data analysis, we can harness the meaning from information littered all around the digital realm. It enables us to resolve the most peculiar inquiries, perhaps even summoning new ones in the process.

Haskell acts as our conduit for robust data analysis. For some, Haskell is a programming language reserved to the most elite researchers in academia and industry. Yet, we see it charming one of the fastest growing cultures of open source developers around the world. The growth of Haskell is a sign that people are uncovering its magnificent functional pureness, resilient type safety, and remarkable expressiveness. Flip the pages of this book to see it all in action.

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