Introduction to Machine Learning

Uday Shankar Shanthamallu, Andreas Spanias

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Scopus citations

Abstract

Machine Learning (ML) [1-4] is a field of science that deals with learning patterns from data features and statistics, without explicit rule-based programming. ML provides an important capability for computers to learn from data examples and experience. A few simple machine learning examples include image classification [5, 6], spam email filtering [7], and stock price prediction [8]. For image classification such as dog vs. cat, an ML model is trained on thousands of images of dogs and cats until it can learn to distinguish the two. Similarly, for spam email filtering, an ML model can be trained with a lot of benign and spam emails to filter future spam messages.

Original languageEnglish (US)
Title of host publicationSynthesis Lectures on Signal Processing
PublisherSpringer Nature
Pages1-8
Number of pages8
DOIs
StatePublished - 2022

Publication series

NameSynthesis Lectures on Signal Processing
ISSN (Print)1932-1236
ISSN (Electronic)1932-1694

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Signal Processing
  • Electrical and Electronic Engineering

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