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Intro Machine Learning D |
Enrollment Information (not real time - data refreshed nightly)
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Class #:
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21672 | |
Enrollment Capacity:
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190 |
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Section:
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D |
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Enrollment Total:
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160 |
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Credits:
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3.00 credits
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Seats Available:
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30 |
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Dates:
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01/30/2023 - 05/12/2023 |
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Status:
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OPEN WITH RESERVES |
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Days, Time:
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T R , 5:00 PM - 6:20 PM |
| Room: |
Knox 110 |
view map |
| Location: |
North Campus |
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| Reserve Capacities |
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| Description |
Enrollment Capacity |
Enrollment Total |
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| Data Sciences & Applics MPS |
130 |
120 |
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| EE MS and EAS IoT Seats Rsvr |
13 |
13 |
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| Eng Sci MS: Robotics Seats Rsv |
45 |
23 |
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| Course Description |
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| Involves teaching computer programs to improve their performance through guided training and unguided experience. Takes both symbolic and numerical approaches. Topics include concept learning, decision trees, neural nets, latent variable models, probabilistic inference, time series models, Bayesian learning, sampling methods, computational learning theory, support vector machines, and reinforcement learning. |
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| Instructor(s) |
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Vereshchaka |
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| On-line Resources |
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| Other Courses Taught By: Vereshchaka |
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