Basics of machine learning

Cambridge University Press eBooks, pp. 14–46

Abstract

In this chapter, we describe basic machine learning concepts connected to optimization and generalization. Moreover, we present a probabilistic view on machine learning that enables us to deal with uncertainty in the predictions we make. Finally, we discuss various basic machine learning models such as support vector machines, neural networks, autoencoders, and autoregressive neural networks. Together, these topics form the machine learning preliminaries needed for understanding the contents of the rest of the book.

Authors 1

1. Borja Requena

   Institute of Photonic Sciences

   Affiliation as printed

   ICFO - The Institute of Photonic Sciences