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AY2025/2026 Semester 1
Overview of machine learning and its applications; Decision Theory and Bayes Models; Classifier Evaluation; Classification: Decision trees, artificial neural networks, linear and kernelized support vector machines, K-nearest neighbour classifiers, linear regression and its kernelized extension; Ensemble Learning; Clustering; Dimension Reduction; Density Estimation; Graphical Models; Applications
| AUs | 3.0 AUs |
| Categories | CoreBDE |
| Not Available To All Programme With | (Admyr 2021-onwards) |
| Mutually Exclusive With | CZ4041, SC4000 |
| Exam |
| Mon | Tue | Wed | Thu | Fri | ||
|---|---|---|---|---|---|---|
| 1030 | COMMON LEC (SCL4) 1030-1220 Tue ONLINE, LT2A Wk10, Teaching Wk1-9,11-13 | COMMON LEC (SCL4) 1030-1220 Tue ONLINE, LT2A Wk10, Teaching Wk1-9,11-13 | ||||
| 1100 | ||||||
| 1130 | ||||||
| 1200 | ||||||
| 1230 | 10820 TUT (SCEL) 1230-1320 Tue ONLINE, LT2A Wk10, Teaching Wk2-9,11-13 | 10820 TUT (SCEL) 1230-1320 Tue ONLINE, LT2A Wk10, Teaching Wk2-9,11-13 | ||||
| 1300 | ||||||
