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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Erscheint auch als (Druck-Ausgabe):

Vuppalapati, Chandrasekar *1972-*. Machine learning and artificial intelligence for agricultural economics. - Cham, Switzerland : Springer, 2022

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