Md. Rezaul Karim - Java Deep Learning Projects: Implement 10 real-world deep learning applications using Deeplearning4j and open source APIs

Copyright 2018 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 or its dealers and distributors, will be held liable for any damages caused or alleged to have been 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.

Commissioning Editor: Sunith Shetty
Acquisition Editor: Tushar Gupta
Content Development Editor: Karan Thakkar
Technical Editor: Dinesh Pawar
Copy Editor: Vikrant Phadkay
Project Coordinator: Nidhi Joshi
Proofreader: Safis Editing
Indexer: Rekha Nair
Graphics: Tania Dutta
Production Coordinator: Arvindkumar Gupta

First published: June 2018

Production reference: 1280618

Published by Packt Publishing Ltd.
Livery Place
35 Livery Street
Birmingham
B3 2PB, UK.

ISBN 978-1-78899-745-4

www.packtpub.com

Mapt is an online digital library that gives you full access to over 5,000 books and videos, as well as industry leading tools to help you plan your personal development and advance your career. For more information, please visit our website.

• Spend less time learning and more time coding with practical eBooks and Videos from over 4,000 industry professionals

• Improve your learning with Skill Plans built especially for you

• Get a free eBook or video every month

• Mapt is fully searchable

• Copy and paste, print, and bookmark content

Did you know that Packt offers eBook versions of every book published, with PDF and ePub files available? You can upgrade to the eBook version at www.PacktPub.com and as a print book customer, you are entitled to a discount on the eBook copy. Get in touch with us at service@packtpub.com for more details.

At www.PacktPub.com , you can also read a collection of free technical articles, sign up for a range of free newsletters, and receive exclusive discounts and offers on Packt books and eBooks.

Md. Rezaul Karim is a Research Scientist at Fraunhofer FIT, Germany. He is also a PhD candidate at RWTH Aachen University, Germany. Before joining FIT, he was a Researcher at Insight Centre for Data Analytics, Ireland. Before that, he was a Lead Engineer at Samsung Electronics, Korea.

He has 9 years of R&D experience in Java, Scala, Python, and R. He has hands-on experience in Spark, Zeppelin, Hadoop, Keras, scikit-learn, TensorFlow, Deeplearning4j, and H2O. He has published several research papers in top-ranked journals/conferences focusing on bioinformatics and deep learning.

Joao Bosco Jares is a Software Engineer with 12 years of experience in machine learning, Semantic Web and IoT. Previously, he was a Software Engineer at IBM Watson, Insight Centre for Data Analytics, Brazilian Northeast Bank, and Bank of Amazonia, Brazil.

He has an MSc and a BSc in computer science, and a data science postgraduate degree. He is also an IBM Jazz RTC Certified Professional, Oracle Certified Master Java EE 6 Enterprise Architect, and Sun Java Certified Programmer.

If you're interested in becoming an author for Packt, please visit authors.packtpub.com and apply today. We have worked with thousands of developers and tech professionals, just like you, to help them share their insight with the global tech community. You can make a general application, apply for a specific hot topic that we are recruiting an author for, or submit your own idea.

The continued growth in data, coupled with the need to make increasingly complex decisions against that data, is creating massive hurdles that prevent organizations from deriving insights in a timely manner using traditional analytical approaches.

To find meaningful values and insights, deep learning evolved, which is a branch of machine learning algorithms based on learning multiple levels of abstraction. Neural networks, being at the core of deep learning, are used in predictive analytics, computer vision, natural language processing, time series forecasting, and performing a myriad of other complex tasks.

Until date, most DL books available are written in Python. However, this book is conceived for developers, data scientists, machine learning practitioners, and deep learning enthusiasts who want to build powerful, robust, and accurate predictive models with the power of Deeplearning4j (a JVM-based DL framework), combining other open source Java APIs.

Throughout the book, you will learn how to develop practical applications for AI systems using feedforward neural networks, convolutional neural networks, recurrent neural networks, autoencoders, and factorization machines. Additionally, you will learn how to attain your deep learning programming on GPU in a distributed way.

After finishing the book, you will be familiar with machine learning techniques, in particular, the use of Java for deep learning, and will be ready to apply your knowledge in research or commercial projects. In summary, this book is not meant to be read cover to cover. You can jump to a chapter that looks like something you are trying to accomplish or one that simply ignites your interest.

Happy reading!

Developers, data scientists, machine learning practitioners, and deep learning enthusiasts who wish to learn how to develop real-life deep learning projects by harnessing the power of JVM-based Deeplearning4j (DL4J), Spark, RankSys, and other open source libraries will find this book extremely useful. A sound understanding of Java is needed. Nevertheless, some basic prior experience of Spark, DL4J, and Maven-based project management will be useful to pick up the concepts quicker.

, Getting Started with Deep Learning, explains some basic concepts of machine learning and artificial neural networks as the core of deep learning. It then briefly discusses existing and emerging neural network architectures. Next, it covers various features of deep learning frameworks and libraries. Then it shows how to solve Titanic survival prediction using a Spark-based Multilayer Perceptron (MLP). Finally, it discusses some frequent questions related to this projects and general DL area.