Antonio Gulli - Deep learning with Keras
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- Book:Deep learning with Keras
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- Year:2017
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BIRMINGHAM - MUMBAI
Copyright 2017 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 2017
Production reference: 1240417
ISBN 978-1-78712-842-2
www.packtpub.com
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Antonio Gulli is a software executive and business leader with a passion for establishing and managing global technological talent, innovation, and execution. He is an expert in search engines, online services, machine learning, information retrieval, analytics, and cloud computing. So far, he has been lucky enough to gain professional experience in four different countries in Europe and managed people in six different countries in Europe and America. Antonio served as CEO, GM, CTO, VP, director, and site lead in multiple fields spanning from publishing (Elsevier) to consumer internet (Ask.com and Tiscali) and high-tech R&D (Microsoft and Google).
I would like to thank Francois Chollet (and the many Keras contributors) for taking the time and effort to build an awesome deep learning toolkit that is easy to use without sacrificing too much power.
I would also like to thank our editors from Packt, Divya Poojari, Cheryl Dsa, and Dinesh Pawar, and our reviewers from Packt and Google, for their support and valuable suggestions. This book would not have been possible without you.
I would like to thank my manager, Brad, and my colleagues Mike and Corrado at Google for encouraging me to write this book, and for their constant help in reviewing the content.
I would like to thank Same Fusy, Herbaciarnia i Kawiarnia in Warsaw. I got the initial inspiration to write this book in front of a cup of tea chosen among hundreds of different offers. This place is magic and I strongly recommend visiting it if you are in search of a place to stimulate creativeness (http://www.samefusy.pl/).
Then I would like to thank HRBP at Google for supporting my wish to donate all of this book's royalties in favor of a minority/diversity scholarship.
I would like to thank my friends Eric, Laura, Francesco, Ettore, and Antonella for supporting me when I was in need. Long-term friendship is a real thing, and you are true friends to me.
I would like to thank my son Lorenzo for encouraging me to join Google, my son Leonardo for his constant passion to discover new things, and my daughter Aurora for making me smile every day of my life. Finally thanks to my father Elio and my mother Maria for their love.
Sujit Pal is a technology research director at Elsevier Labs, working on building intelligent systems around research content and metadata. His primary interests are information retrieval, ontologies, natural language processing, machine learning, and distributed processing. He is currently working on image classification and similarity using deep learning models. Prior to this, he worked in the consumer healthcare industry, where he helped build ontology-backed semantic search, contextual advertising, and EMR data processing platforms. He writes about technology on his blog at Salmon Run.
I would like to thank Ron Daniel, the director of Elsevier Labs, and Bradley P Allen, chief architect at Elsevier, for introducing me to deep learning and making me a believer in its capabilities.
I would also like to thank Francois Chollet (and the many Keras contributors) for taking the time and effort to build an awesome deep learning toolkit that is easy to use without sacrificing too much power.
Thanks to our editors from Packt, Divya Poojari, Cheryl Dsa, and Dinesh Pawar, and our reviewers from Packt and Google, for their support and valuable suggestions. This book would not have been possible without you.
I would like to thank my colleagues and managers over the years, especially the ones who took their chances with me and helped me make discontinuous changes in my career.
Finally, I would like to thank my family for putting up with me these past few months as I juggled work, this book, and family, in that order. I hope you will agree that it was all worth it.
Nick McClure is currently a senior data scientist at PayScale Inc. in Seattle, Washington, USA. Prior to that, he worked at Zillow and Caesars Entertainment. He got his degrees in applied mathematics from the University of Montana and the College of Saint Benedict and Saint John's University. Nick has also authored TensorFlow Machine Learning Cookbook by Packt Publishing.
He has a passion for learning and advocating for analytics, machine learning, and artificial intelligence. Nick occasionally puts his thoughts and musing on his blog, fromdata.org, or through his Twitter account at @nfmcclure.
For support files and downloads related to your book, please visit www.PacktPub.com .
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