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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 MACH LRN FOR ENV ENG & SC | |
| Call Number | 10020 |
| Day & Time Location |
W 4:10pm-6:40pm 1024 Seeley W. Mudd Building |
| Points | 3 |
| Grading Mode | Standard |
| Approvals Required | None |
| Instructor | Pierre Gentine |
| Type | LECTURE |
| 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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