id
	15879
Url
	https://chloe.cnr.it/s/BiDiAr/item/15879
Resource template
	Academic Article
Resource class
	bibo:AcademicArticle
Title
	Machine Learning Arrives in Archaeology
Creator
	Bickler, Simon H.
Date
	2021
Language
	eng
Abstract
	Machine learning (ML) is rapidly being adopted by archaeologists interested in analyzing a range of geospatial, material cultural, textual, natural, and artistic data. The algorithms are particularly suited toward rapid identification and classification of archaeological features and objects. The results of these new studies include identification of many new sites around the world and improved classification of large archaeological datasets. ML fits well with more traditional methods used in archaeological analysis, and it remains subject to both the benefits and difficulties of those approaches. Small datasets associated with archaeological work make ML vulnerable to hidden complexity, systemic bias, and high validation costs if not managed appropriately. ML's scalability, flexibility, and rapid development, however, make it an essential part of twenty-first-century archaeological practice. This review briefly describes what ML is, how it is being used in archaeology today, and where it might be used in the future for archaeological purposes.
Is Part Of
	Advances in Archaeological Practice
Doi
	https://doi.org/10.1017/aap.2021.6
Issn
	2326-3768
Issue
	2
Pages
	186-191
Uri
	https://www.cambridge.org/core/journals/advances-in-archaeological-practice/article/machine-learning-arrives-in-archaeology/418D14FD3BAA55A550D61D710A9A8CE0
Volume
	9
Homepage
	https://www.zotero.org/groups/5293298/bidiar/items/GXDXB5GG/item-list

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