This course gives an overall view of the modern statistical/machine learning techniques for mining massive datasets, ranging from generalized linear models, over model selection, to the state-of-the-art techniques like LASSO, neural networks, etc. This course will not only discuss individual algorithms and methods, but also tie principles and approaches together from a theoretical perspective. Moreover, students can gain a hands-on experience through team project. This course equips students with the necessary skills for being a data analyst.
Academic Units | 4 |
Exam Schedule | Not Applicable |
Grade Type | Letter Graded |
Department Maintaining | MATH(SPS) |
Prerequisites | |
Mutually Exclusive | |
Not Available to Programme | EEE, EEEC, IEEC, IEM |
Index | Type | Group | Day | Time | Venue | Remark |
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0930
1030
1130
1230
1330
1430
1530
1630
1730
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