Machine Learning and Artificial Intelligence for Agricultural Economics : Prognostic Data Analytics to Serve Small Scale Farmers Worldwide

by Chandrasekar Vuppalapati

1. Introduction -- 2. Data Engineering and Exploratory Data Analysis Techniques -- 3. Agricultural Economy and ML Models -- 4. Commodity Markets - Machine Learning Techniques -- 5. Weather Patterns and Machine Learning -- 6. Agriculture Employment and the Role of AI in improving Productivity -- 7. Role of Government and the AI Readiness -- 8. Future.

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Year of publication:	2021 ; 1st ed. 2021.
Authors:	Vuppalapati, Chandrasekar
Publisher:	2021.: Cham : Springer International Publishing 2021.: Cham : Imprint: Springer
Subject:	Landwirtschaft \| Agriculture \| Künstliche Intelligenz \| Artificial intelligence \| Agrarpolitik \| Agricultural policy \| Kleinbauern \| Smallholders \| Welt \| World

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Extent:	1 Online-Ressource(XIX, 599 p. 317 illus., 286 illus. in color.)
Series:	International Series in Operations Research & Management Science ; 314
Type of publication:	Book / Working Paper
Language:	English
ISBN:	978-3-030-77485-1 ; 978-3-030-77484-4 ; 978-3-030-77486-8 ; 978-3-030-77487-5
Other identifiers:	10.1007/978-3-030-77485-1 [DOI]
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10012694989