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

Summary


In this chapter, we went from the example of AlphaGo as breaking news to the consideration of how deep learning will or should develop. A machine winning over a human in some areas is not worthy of fear, but is an opportunity for humans to grow as well. On the other hand, it is quite possible that this great technology could go in the wrong direction, as seen in the example of Tay, if the technology of AI isn't handled appropriately. Therefore, we should be careful not to destroy this steadily developing technology.

The field of deep learning is one that has the potential for hugely changing an era with just one idea. If you build AI in the near future, that AI is, so to speak, a pure existence without any knowledge. Thinking what to teach AI, how to interact with it, and how to make use of AI for humankind is humans' work. You, as a reader of this book, will lead a new technology in the right direction. Lastly, I hope you will get actively involved in the cutting edge of the field...