Machine learning for planetary science /

"Machine Learning for Planetary Science presents planetary scientists with a way to introduce machine learning into the research workflow as increasingly large nonlinear datasets are acquired from planetary exploration missions. The book explores research that leverages machine learning methods...

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Bibliographic Details

Corporate Author:	ScienceDirect (Online service)
Other Authors:	Helbert, Joern (Editor), D'Amore, Mario (Editor), Aye, Michael (Editor), Kerner, Hannah (Editor)
Format:	eBook
Language:	English
Published:	Amsterdam : Elsevier, 2022.
Subjects:	Planetary science > Data processing. Machine learning. Planétologie > Informatique. Apprentissage automatique. Machine learning Electronic books.
Online Access:	Connect to the full text of this electronic book