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
About the Author
About the Reviewers
Other Important Deep Learning Libraries

Chapter 8. What's Next?

In the previous chapters, we learned the concept, theory, implementation of deep learning, and how to use libraries. Now you know the basic technique of deep learning, so don't worry. On the other hand, development of deep learning is rapid and a new model might be developed tomorrow. Big news about AI or deep learning comes out one after the other every day. Since you have acquired the basic technique, you can learn about the upcoming new technologies on AI and deep learning quickly. Now, let's walk away from the details of techniques and think about what path the field of AI will or should take. What is the future of deep learning? For the closing chapter, let's think about that. We'll pick up the following topics in this chapter:

  • Hot topics in the deep learning industry

  • How to manage AI technologies

  • How to proceed the study of deep learning further

As for the last topic, about further study, I will recommend a website about deep learning. You can stay ahead of the...