Chapter 1, Deep Learning Overview, explores how deep learning has evolved.

Chapter 2, Algorithms for Machine Learning - Preparing for Deep Learning, implements machine learning algorithms related to deep learning.

Chapter 3, Deep Belief Nets and Stacked Denoising Autoencoders, dives into Deep Belief Nets and Stacked Denoising Autoencoders algorithms.

Chapter 4, Dropout and Convolutional Neural Networks, discovers more deep learning algorithms with Dropout and Convolutional Neural Networks.

Chapter 5, Exploring Java Deep Learning Libraries – DL4J, ND4J, and More, gains an insight into the deep learning library, DL4J, and its practical uses.

Chapter 6, Approaches to Practical Applications – Recurrent Neural Networks and More, lets you devise strategies to use deep learning algorithms and libraries in the real world.

Chapter 7, Other Important Deep Learning Libraries, explores deep learning further with Theano, TensorFlow, and Caffe.

Chapter 8, What's Next?, explores recent deep learning movements and events, and looks into useful deep learning resources.

We'll implement deep learning algorithms using Lambda Expressions, hence Java 8 or above is required. Also, we'll use the Java library DeepLearning4J 0.4 or above.

This book is for Java developers who want to know about deep learning algorithms and wish to implement them in applications.

Since this book covers the core concepts of and approaches to both machine learning and deep learning, no previous experience in machine learning is required.

Also, we will implement deep learning algorithms with very simple codes, so elementary Java developers will also find this book useful for developing both their Java skills and deep learning skills.

In this book, you will find a number of text styles that distinguish between different kinds of information. Here are some examples of these styles and an explanation of their meaning.

Code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles are shown as follows: "Let's take a look at CNNMnistExample.java in the package of convolution."

A block of code is set as follows:

<dependency>
   <groupId>org.nd4j</groupId>
   <artifactId>nd4j-jcublas-7.0</artifactId>
   <version>${nd4j.version}</version>
</dependency>

Any command-line input or output is written as follows:

[[7.00,7.00]
 [7.00,7.00]
 [7.00,7.00]]

New terms and important words are shown in bold. Words that you see on the screen, for example, in menus or dialog boxes, appear in the text like this: "If you're using IntelliJ, you can import the project from File | New | Project from existing sources."

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To send us general feedback, simply e-mail <[email protected]>, and mention the book's title in the subject of your message.

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