Module code: MTH793P
Credits: 15.0
Semester: SEM2
Contact: Dr Hong Qi
Prerequisite: Before or while taking this module you must take MTH786P
This module builds on the earlier module 'Machine Learning with Python', covering a number of advanced techniques in machine learning, such as different methods for clustering, dimensionality reduction, matrix completion, and autoencoders. Although the underlying theoretical ideas are clearly explained, this module is very hands-on, and you will implement various applications using Python in the weekly coursework assignments.
Connected course(s): UDF DATA
Assessment: 60.0% Coursework, 40.0% Examination
Level: 7
