Book Image

Java Deep Learning Essentials

By : Yusuke Sugomori
Book Image

Java Deep Learning Essentials

By: Yusuke Sugomori

Overview of this book

AI and Deep Learning are transforming the way we understand software, making computers more intelligent than we could even imagine just a decade ago. Deep Learning algorithms are being used across a broad range of industries – as the fundamental driver of AI, being able to tackle Deep Learning is going to a vital and valuable skill not only within the tech world but also for the wider global economy that depends upon knowledge and insight for growth and success. It’s something that’s moving beyond the realm of data science – if you’re a Java developer, this book gives you a great opportunity to expand your skillset. Starting with an introduction to basic machine learning algorithms, to give you a solid foundation, Deep Learning with Java takes you further into this vital world of stunning predictive insights and remarkable machine intelligence. Once you’ve got to grips with the fundamental mathematical principles, you’ll start exploring neural networks and identify how to tackle challenges in large networks using advanced algorithms. You will learn how to use the DL4J library and apply Deep Learning to a range of real-world use cases. Featuring further guidance and insights to help you solve challenging problems in image processing, speech recognition, language modeling, this book will make you rethink what you can do with Java, showing you how to use it for truly cutting-edge predictive insights. As a bonus, you’ll also be able to get to grips with Theano and Caffe, two of the most important tools in Deep Learning today. By the end of the book, you’ll be ready to tackle Deep Learning with Java. Wherever you’ve come from – whether you’re a data scientist or Java developer – you will become a part of the Deep Learning revolution!
Table of Contents (15 chapters)
Java Deep Learning Essentials
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
7
Other Important Deep Learning Libraries
Index

Chapter 1. Deep Learning Overview

Artificial Intelligence (AI) is a word that you might start to see more often these days. AI has become a hot topic not only in academic society, but also in the field of business. Large tech companies such as Google and Facebook have actively bought AI-related start-ups. Mergers and acquisitions in these AI areas have been especially active, with big money flowing into AI. The Japanese IT/mobile carrier company Softbank released a robot called Pepper in June 2014, which understands human feelings, and a year later they have started to sell Pepper to general consumers. This is a good movement for the field of AI, without a doubt.

The idea of AI has been with us for decades. So, why has AI suddenly became a hot field? One of the factors that has driven recent AI-related movements, and is almost always used with the word AI, is deep learning. After deep learning made a vivid debut and its technological capabilities began to grow exponentially, people started to think that finally AI would become a reality. It sounds like deep learning is definitely something we need to know. So, what exactly is it?

To answer the previous questions, in this chapter we'll look at why and how AI has become popular by following its history and fields of studies. The topics covered will be:

  • The former approaches and techniques of AI

  • An introduction to machine learning and a look at how it has evolved into deep learning

  • An introduction to deep learning and some recent use cases

If you already know what deep learning is or if you would like to find out about the specific algorithm of the deep learning/implementation technique, you can skip this chapter and jump directly to Chapter 2, Algorithms for Machine Learning – Preparing for Deep Learning.

Although deep learning is an innovative technique, it is not actually that complicated. It is rather surprisingly simple. Reading through this book, you will see how brilliant it is. I sincerely hope that this book will contribute to your understanding of deep learning and thus to your research and business.