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NOTE: Course information changes frequently, including Methods of Instruction. Please revisit these pages periodically for the most recent and up-to-date course information.

Fall 2022 Earth and Environmental Engineering E4000 section 001
Machine learning for environmental engin

Call Number 10020
Day & Time
W 4:10pm-6:40pm
1024 Seeley W. Mudd Building
Points 3
Grading Mode Standard
Approvals Required None
Instructor Pierre Gentine
Method of Instruction In-Person
Course Description Aimed at understanding and testing state-of?the-art methods in machine learning applied to environmental sciences and engineering problems. Potential applications include but are not limited to remote sensing, and environmental and geophysical fluid dynamics. Includes testing "vanilla" ML algorithms, feedforward neural networks, random forests, shallow vs deep networks, and the details of machine learning techniques.
Web Site Vergil
Department Earth and Environmental Engineering
Enrollment 51 students (55 max) as of 7:07PM Tuesday, March 21, 2023
Subject Earth and Environmental Engineering
Number E4000
Section 001
Division School of Engineering and Applied Science: Graduate
Campus Morningside
Section key 20223EAEE4000E001

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SIS update 03/21/23 19:07    web update 03/21/23 19:18