| Call Number | 11525 |
|---|---|
| Day & Time Location |
W 4:10pm-6:40pm 1127 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 | 48 students (50 max) as of 12:07PM Monday, April 29, 2024 |
| Subject | Earth and Environmental Engineering |
| Number | E4000 |
| Section | 001 |
| Division | School of Engineering and Applied Science: Graduate |
| Campus | Morningside |
| Section key | 20233EAEE4000E001 |