Chapter 3. Perceptrons and Supervised Learning
In this chapter, we are going to explore in more detail supervised learning, which is very useful in finding relations between two datasets. Also, we introduce perceptrons, a very popular neural network architecture that implements supervised learning. This chapter also presents their extended generalized version, the so-called multi-layer perceptrons, as well as their features, learning algorithms, and parameters. Also, the reader will learn how to implement them in Java and how to use them in solving some basic problems. This chapter will cover the following topics:
- Supervised learning
- Regression tasks
- Classification tasks
- Perceptrons
- Linear separation
- Limitations: the XOR problem
- Multilayer perceptrons ...
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