This course introduces basic concepts and methodologies for machine learning as well as their applications.
Clustering.
Dimension Reduction.
Classification.
Decision Theory.
Density Estimation.
Classifier Evaluation.
Prerequisite graph
Required first
CZ1007Data StructuresCZ1011Engineering Mathematics ICZ1107Data Structures & AlgorithmsCZ2100Probability & Statistics For ComputingMH2500ProbabilityMachine Learning
Unlocks
Available indexes
| Mon | Tue | Wed | Thu | Fri | |
|---|---|---|---|---|---|
| 1230 | 10708 TUT (SCEL) 1230-1320 Mon LT20 Wk2-13 | ||||
| 1300 | |||||
| 1330 | |||||
| 1400 | |||||
| 1430 | COMMON LEC (SCL4) 1430-1620 Wed LT19 | ||||
| 1500 | |||||
| 1530 | |||||
| 1600 |
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