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Designing Machine Learning Systems with Python 2016 {PRG}
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Designing Machine Learning Systems with Python 2016 {PRG} Designing Machine Learning Systems with Python 2016 {PRG}
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Designing Machine Learning Systems with Python
Copyright © 2016 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: April 2016
Production reference: 1310316
Published by Packt Publishing Ltd.
Livery Place
35 Livery Street
Birmingham B3 2PB, UK.
ISBN 978-1-78588-295-1
www.packtpub.com
Credits
Author
David Julian
Reviewer
Dr. Vahid Mirjalili
Commissioning Editor
Veena Pagare
Acquisition Editor
Tushar Gupta
Content Development Editor
Merint Thomas Mathew
Technical Editor
Abhishek R. Kotian
Copy Editor
Angad Singh
Project Coordinator
Suzanne Coutinho
Proofreader
Sas Editing
Indexer
Rekha Nair
Graphics
Disha Haria
Jason Monteiro
Production Coordinator
Aparna Bhagat
Cover Work
Aparna Bhagat
About the Author
David Julian
is currently working on a machine learning project with Urban
Ecological Systems Ltd and Blue Smart Farms (
http://www.bluesmartfarms.
com.au
) to detect and predict insect infestation in greenhouse crops. He is currently
collecting a labeled training set that includes images and environmental data
(temperature, humidity, soil moisture, and pH), linking this data to observations of
infestation (the target variable), and using it to train neural net models. The aim is to
create a model that will reduce the need for direct observation, be able to anticipate
insect outbreaks, and subsequently control conditions. There is a brief outline of
the project at
http://davejulian.net/projects/ues
. David also works as a data
analyst, I.T. consultant, and trainer.
I would like to thank Hogan Gleeson, James Fuller, Kali McLaughlin
and Nadine Miller. This book would not have been possible without
the great work of the open source machine learning community.
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