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SDSC4016 - Fundamentals of Machine Learning II

Offering Academic Unit
School of Data Science
Credit Units
3
Course Duration
One Semester
Pre-requisite(s)
Course Offering Term*:
Semester B 2021/22
Semester B 2022/23 (Tentative)

* The offering term is subject to change without prior notice
 
Course Aims

This elective course provides students who have the basic foundations of machine learning with an intensive studies of advanced machine learning techniques for data science. Topics include linear model selection and regularization, kernel-based methods and kernel tricks, model assessment and selection, neural network models and computational learning theory.


Assessment (Indicative only, please check the detailed course information)

Continuous Assessment: 60%
Examination: 40%
(24-hour open-book taken-home programming exam)
 
Detailed Course Information

SDSC4016.pdf

Useful Links

School of Data Science