This chapter presented a brief introduction to neural networks and deep neural networks. Using multiple hidden layers, deep neural networks have been a revolution in machine learning. They consistently outperform other machine learning tasks, especially in areas such as computer vision, natural-language processing, and speech-recognition.
The chapter also looked at some of the theory behind neural networks, the difference between shallow neural networks and deep neural networks, and some of the misconceptions that currently exist concerning deep learning.
We closed this chapter with a discussion on how to set up R and the importance of using a GUI (RStudio). This section discussed the deep learning libraries available in R (MXNet, Keras, and TensorFlow), GPUs, and reproducibility.
In the next chapter, we will begin to train neural networks and generate our own predictions.
