In Chapter 1, Machine Learning – an Introduction, we introduced a number of basic machine learning(ML) concepts and techniques. We went through the main ML paradigms, as well as some popular classic ML algorithms, and we finished with neural networks. In this chapter, we will formally introduce what neural networks are, describe in detail how a neuron works, see how we can stack many layers to create a deep feedforward neural network, and then we'll learn how to train them.
In this chapter, we will cover the following topics:
- The need for neural networks
- An introduction to neural networks
- Training neural networks
Initially, neural networks were inspired by the biological brain (hence the name). Over time, however, we've stopped trying to emulate how the brain works and instead we focused on finding the correct configurations for specific tasks...
