Introduction to Machine Learning

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review


As already discussed in Chap. 1, Machine Learning (ML) (Mitchell, 1997; Shalev-Shwartz and Ben-David, 2014) is a field of study whose objective is to program computers to automatically learn to solve a problem, or accomplish a task. ML is useful when manually programming a computer to carry out a task is either impractical or infeasible. Typical cases are either problems that are so complex that they are beyond human capabilities, like those characterized by vast amounts of data, or tasks that living beings perform routinely, but our introspection on how we do it is not sufficiently elaborated to allow us to extract a well-defined algorithm, for instance driving, speech recognition, image understanding or client categorization.

Original languageEnglish
Title of host publicationLectures on Intelligent Systems
Place of PublicationCham, Switzerland
PublisherSpringer, Cham
Number of pages34
ISBN (Electronic)978-3-031-17922-8
ISBN (Print)978-3-031-17921-1, 978-3-031-17924-2
Publication statusPublished - 13 Jan 2023

Publication series

NameNatural Computing Series
ISSN (Print)1619-7127


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