Not offered in the current semester · Last offered AY2025/2026 Semester 2
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
Prerequisite Graph
Required first
CE1011Engineering Mathematics ICE1107Data Structures & AlgorithmsCE2100Probability & Statistics For ComputingCE4041
Machine Learning
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Available Indexes
| Mon | Tue | Wed | Thu | Fri | |
|---|---|---|---|---|---|
| 1230 | 10808 TUT (SCEL) 1230-1320 Mon LT20 Wk2-13 | ||||
| 1300 | |||||
| 1330 | |||||
| 1400 | |||||
| 1430 | COMMON LEC (SCL4) 1430-1620 Wed LT19 | ||||
| 1500 | |||||
| 1530 | |||||
| 1600 |
Other offerings
AY25/26
AY24/25
AY23/24
AY22/23
AY21/22
AY20/21
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