Giancarlo Zaccone - Getting started with tensorflow : get up and running with the latest numerical computing library by Google and dive deeper into your data!
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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: July 2016
Production reference: 1190716
Published by Packt Publishing Ltd.
Livery Place
35 Livery Street
Birmingham
B3 2PB, UK.
ISBN 978-1-78646-857-4
www.packtpub.com
Author Giancarlo Zaccone | Copy Editor Alpha Singh |
Reviewer Jayani Withanawasam | Project Coordinator Shweta H Birwatkar |
Commissioning Editor Veena Pagare | Proofreader Safis Editing |
Acquisition Editor Vinay Argekar | Indexer Mariammal Chettiyar |
Content Development Editor Sumeet Sawant | Production Coordinator Nilesh Mohite |
Technical Editor Deepti Tuscano | Cover Work Nilesh Mohite |
Giancarlo Zaccone has more than 10 years of experience managing research projects in both the scientific and industrial domains. He worked as researcher at the C.N.R, the National Research Council, where he was involved in projects related to parallel numerical computing and scientific visualization.
Currently, he is a senior software engineer at a consulting company developing and maintaining software systems for space and defence applications.
Giancarlo holds a master's degree in physics from the Federico II of Naples and a 2nd level postgraduate master course in scientific computing from La Sapienza of Rome.
He has already been a Packt author for the following book: Python Parallel Programming Cookbook.
You can contact him at https://it.linkedin.com/in/giancarlozaccone
Jayani Withanawasam is a senior software engineer at Zaizi Asia - Research and Development team. She is the author of the book Apache Mahout Essentials , on scalable machine learning. She was a summit speaker at Alfresco Summit 2014 - London. Her talk was about applications of machine learning techniques in smart enterprise content management (ECM) solutions. She presented her research Content Extraction and Context Inference based Information Retrieval at the Women in Machine Learning (WiML) 2015 workshop, which was co-located with the Neural Information Processing Systems (NIPS) 2015 conference - Montreal, Canada.
Jayani is currently pursuing an MSc in Artificial Intelligence at the University of Moratuwa, Sri Lanka. She has strong research interests in machine learning and computer vision.
You can contact her at https://lk.linkedin.com/in/jayaniwithanawasam
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TensorFlow is an open source software library used to implement machine learning and deep learning systems.
Behind these two names are hidden a series of powerful algorithms that share a common challenge: to allow a computer to learn how to automatically recognize complex patterns and make the smartest decisions possible.
Machine learning algorithms are supervised or unsupervised; simplifying as much as possible, we can say that the biggest difference is that in supervised learning the programmer instructs the computer how to do something, whereas in unsupervised learning the computer will learn all by itself.
Deep learning is instead a new area of machine learning research that has been introduced with the objective of moving machine learning closer to artificial intelligence goals. This means that deep learning algorithms try to operate like the human brain.
With the aim of conducting research in these fascinating areas, the Google team developed TensorFlow, which is the subject of this book.
To introduce TensorFlows programming features, we have used the Python programming language. Python is fun and easy to use; it is a true general-purpose language and is quickly becoming a must-have tool in the arsenal of any self-respecting programmer.
It is not the aim of this book to completely describe all TensorFlow objects and methods; instead we will introduce the important system concepts and lead you up the learning curve as fast and efficiently as we can. Each chapter of the book presents a different aspect of TensorFlow, accompanied by several programming examples that reflect typical issues of machine and deep learning.
Although it is large and complex, TensorFlow is designed to be easy to use once you learn about its basic design and programming methodology.
The purpose of Getting Started with TensorFlow is to help you do just that.
Enjoy reading!
Chapter 1 , TensorFlow Basic Concepts, contains general information on the structure of TensorFlow and the issues for which it was developed. It also provides the basic programming guidelines for the Python language and a first TensorFlow working session after the installation procedure. The chapter ends with a description of TensorBoard, a powerful tool for optimization and debugging.
Chapter 2 , Doing Math with TensorFlow, describes the ability of mathematical processing of TensorFlow. It covers programming examples on basic algebra up to partial differential equations. Also, the basic data structure in TensorFlow, the tensor
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