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 2. Algorithms for Machine Learning – Preparing for Deep Learning

In the previous chapter, you read through how deep learning has been developed by looking back through the history of AI. As you should have noticed, machine learning and deep learning are inseparable. Indeed, you learned that deep learning is the developed method of machine learning algorithms.

In this chapter, as a pre-exercise to understand deep learning well, you will see the mode details of machine learning, and in particular, you will learn the actual code for the method of machine learning, which is closely related to deep learning.

In this chapter, we will cover the following topics:

  • The core concepts of machine learning

  • An overview of popular machine learning algorithms, especially focusing on neural networks

  • Theories and implementations of machine learning algorithms related to deep learning: perceptrons, logistic regression, and multi-layer perceptrons