Chapter 11. Deep learning
Until now, we covered a few supervised, semi-supervised, unsupervised, and reinforcement learning techniques and algorithms. In this chapter, we will cover neural networks and its relationship with the deep learning practices. The traditional learning approach was about writing programs that tell the computer what to do, but neural networks are about learning and finding solutions using observational data that forms a primary source of input. This technique's success depends on how the neural networks are trained (that is, the quality of the observational data). Deep learning refers to methods of learning the previously referenced neural networks.
The advancement in technology has taken these techniques to new heights where these techniques demonstrate superior performance, and are used to solve some key non-trivial requirements in computer vision, speech recognition, and Natural Language Processing (NLP). Large companies such as Facebook and Google, among many...
