Reinforcement Learning for Data Science

Jonatan Barkan, Michal Moran, Goren Gordon*

*Corresponding author for this work

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

Abstract

In the realm of data science, where big data abound, most machine learning methods fall into one of the two categories: supervised learning in which labeled data exist, i.e., for each input in the dataset there is a known output; unsupervised learning in which no label exists and patterns in the data are sought after.

Original languageEnglish
Title of host publicationMachine Learning for Data Science Handbook
Subtitle of host publicationData Mining and Knowledge Discovery Handbook, Third Edition
PublisherSpringer International Publishing
Pages537-557
Number of pages21
ISBN (Electronic)9783031246289
ISBN (Print)9783031246272
DOIs
StatePublished - 1 Jan 2023

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