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Garner - Clojure for Data Science

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Garner Clojure for Data Science
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Clojure for Data Science: summary, description and annotation

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Statistics, big data, and machine learning for Clojure programmers

About This Book

  • Write code using Clojure to harness the power of your data
    • Discover the libraries and frameworks that will help you succeed
    • A practical guide to understanding how the Clojure programming language can be used to derive insights from data

      Who This Book Is For

      This book is aimed at developers who are already productive in Clojure but who are overwhelmed by the breadth and depth of understanding required to be effective in the field of data science. Whether youre tasked with delivering a specific analytics project or simply suspect that you could be deriving more value from your data, this book will inspire you with the opportunitiesand inform you of the risksthat exist in data of all shapes and sizes.

      What You Will Learn

    • Perform hypothesis testing and understand feature selection and statistical significance to interpret your results with...
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    Clojure for Data Science

    Clojure for Data Science

    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: September 2015

    Production reference: 1280815

    Published by Packt Publishing Ltd.

    Livery Place

    35 Livery Street

    Birmingham B3 2PB, UK.

    ISBN 978-1-78439-718-0

    www.packtpub.com

    Credits

    Author

    Henry Garner

    Reviewer

    Dan Hammer

    Commissioning Editor

    Ashwin Nair

    Acquisition Editor

    Meeta Rajani

    Content Development Editor

    Shubhangi Dhamgaye

    Technical Editor

    Shivani Kiran Mistry

    Copy Editor

    Akshata Lobo

    Project Coordinator

    Harshal Ved

    Proofreader

    Safis Editing

    Indexer

    Monica Ajmera Mehta

    Graphics

    Nicholas Garner

    Disha Haria

    Production Coordinator

    Arvindkumar Gupta

    Cover Work

    Arvindkumar Gupta

    About the Author

    Henry Garner is a graduate from the University of Oxford and an experienced developer, CTO, and coach.

    He started his technical career at Britain's largest telecoms provider, BT, working with a traditional data warehouse infrastructure. As a part of a small team for 3 years, he built sophisticated data models to derive insight from raw data and use web applications to present the results. These applications were used internally by senior executives and operatives to track both business and systems performance.

    He then went on to co-found Likely, a social media analytics start-up. As the CTO, he set the technical direction, leading to the introduction of an event-based append-only data pipeline modeled after the Lambda architecture. He adopted Clojure in 2011 and led a hybrid team of programmers and data scientists, building content recommendation engines based on collaborative filtering and clustering techniques. He developed a syllabus and copresented a series of evening classes from Likely's offices for professional developers who wanted to learn Clojure.

    Henry now works with growing businesses, consulting in both a development and technical leadership capacity. He presents regularly at seminars and Clojure meetups in and around London.

    Acknowledgments

    Thank you Shubhangi Dhamgaye, Meeta Rajani, Shivani Mistry, and the entire team at Packt for their help in bringing this project to fruition. Without you, this book would never have come to pass.

    I'm grateful to Dan Hammer, my Packt reviewer, for his valuable perspective as a practicing data scientist, and to those other brave souls who patiently read through the very rough early (and not-so-early) drafts. Foremost among these are lonore Mayola, Paul Butcher, and Jeremy Hoyland. Your feedback was not always easy to hear, but it made the book so much better than it would otherwise have been.

    Thank you to the wonderful team at MastodonC who tackled a pre-release version of this book in their company book club, especially lonore Mayola, Jase Bell, and Elise Huard. I'm grateful to Francine Bennett for her advice early onwhich helped to shape the structure of the bookand also to Bruce Durling, Neale Swinnerton, and Chris Adams for their company during the otherwise lonely weekends spent writing in the office.

    Thank you to my friends from the machine learning study group: Sam Joseph, Geoff Hogg, and Ben Taylor for reading the early drafts and providing feedback suitable for Clojure newcomers; and also to Luke Snape and Tom Coupland of the Bristol Clojurians for providing the opportunity to test the material out on its intended audience.

    A heartfelt thanks to my dad, Nicholas, for interpreting my vague scribbles into the fantastic figures you see in this book, and to my mum, Jacqueline, and sister, Mary, for being such patient listeners in the times I felt like thinking aloud. Last, but by no means least, thank you to the Nuggets of Wynford Road, Russell and Wendy, for the tea and sympathy whenever it occasionally became a bit too much. I look forward to seeing much more of you both from now on.

    About the Reviewer

    Dan Hammer is a presidential innovation fellow working on Data Innovation initiatives at the NASA headquarters in the CTO's office. Dan is an economist and data scientist. He was the chief data scientist at the World Resources Institute, where he launched Global Forest Watch in partnership with Google, USAID, and many others. Dan is on leave from a PhD program at UC Berkeley, as advised by Max Auffhammer and George Judge. He teaches mathematics at the San Quentin State Prison as a lead instructor with the Prison University Project. Dan graduated with high honors in economics and mathematics from Swarthmore College, where he was a language scholar. He spent a full year building and racing Polynesian outrigger canoes in the South Pacific as a Watson Fellow. He has also reviewed Learning R for Geospatial Analysis by Packt Publishing.

    Thanks to my wonderful wife Emily for suffering through my terrible jokes.

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    For Helen.

    You provided support, encouragement, and welcome distraction in roughly equal measure.

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