SDSC8003 - Machine Learning | ||||||||
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| * The offering term is subject to change without prior notice | ||||||||
Course Aims | ||||||||
This course provides students with an extensive exposure to machine learning. Topics include theory of uniform convergence, generalization analysis of learning algorithms for regression and classification, kernel methods, analysis of online learning and distributed learning, and some unsupervised learning methods such as clustering and dimensionality reduction. | ||||||||
Assessment (Indicative only, please check the detailed course information) | ||||||||
Continuous Assessment: 40% | ||||||||
Examination: 60% | ||||||||
Examination Duration: 2 hours | ||||||||
Detailed Course Information | ||||||||
| SDSC8003.pdf | ||||||||
Useful Links | ||||||||
| School of Data Science | ||||||||
