Module code: MTH6101
Credits: 15.0
Semester: SEM1
Contact: Dr Konstantinos Papafitsoros
Prerequisite: Before taking this module you must take MTH5120
Machine Learning is a rapidly growing field, at the boundary between Statistics and Computer Science. This course gives an understanding of the theoretical basis for machine learning and a set of concrete algorithms including decision tree learning and classification methods. Moreover, this course will introduce some classical statistical methods for high-dimensional data. The course also includes programming and use of algorithms on concrete data set.
Connected course(s): UDF DATA
Assessment: 70.0% Examination, 30.0% Coursework
Level: 6
