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Statistical Learning I BROD |
Enrollment Information (not real time - data refreshed nightly)
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Class #:
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22220 | |
Enrollment Capacity:
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66 |
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Section:
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BROD |
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Enrollment Total:
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66 |
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Credits:
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3.00 credits
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Seats Available:
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0 |
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Dates:
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08/29/2022 - 12/09/2022 |
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Status:
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CLOSED |
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Days, Time:
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T R , 11:00 AM - 12:20 PM |
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Obrian 109 |
view map |
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North Campus |
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| Reserve Capacities |
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| Description |
Enrollment Capacity |
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| Eng Sci MS Data Sci Seats Rsvr |
66 |
66 |
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| Course Description |
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| An introduction to the mathematical theory and computational methodology at the heart of statistical learning. This first semester considers supervised learning, including topics classification -- support vector machines, k-nearest neighbors, Naive Bayes, logistic regression, tree methods and forests, bagging and ensemble methods, GPs and neural networks -- and methods for validation and testing. R programming will be used. Prerequisite experience: EAS MS-DS student, or MTH 142, MTH 309, MTH 411 or equivalent, or permission of instructor. |
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| Instructor(s) |
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Broderick |
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| On-line Resources |
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| Other Courses Taught By: Broderick |
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