Java Deep Learning Essentials

Chapter 3. Deep Belief Nets and Stacked Denoising Autoencoders

From this chapter through to the next chapter, you are going to learn the algorithms of deep learning. We'll follow the fundamental math theories step by step to fully understand each algorithm. Once you acquire the fundamental concepts and theories of deep learning, you can easily apply them to practical applications.

In this chapter, the topics you will learn about are:

• Reasons why deep learning could be a breakthrough
• The differences between deep learning and past machine learning (neural networks)
• Theories and implementations of the typical algorithms of deep learning, deep belief nets (DBN), and Stacked Denoising Autoencoders (SDA)

Neural networks fall

In the previous chapter, you learned ...