Machine Learning with Python

Module code: MTH786P

Credits: 15.0
Semester: SEM1

Contact: Dr Nicola Perra

This module will introduce you to some of the most widely-used techniques in machine learning (ML). After reviewing the necessary background mathematics, we will investigate various ML methods, such as linear regression, polynomial regression, neural networks, classification with logistic regression, support vector machines and decision trees. The module covers a very wide range of practical applications, with an emphasis on hands-on numerical work using Python. At the end of the module, you will be able to formalise a ML task, choose the appropriate method to process it numerically, implement the ML algorithm in Python, and assess the method's performance.

Connected course(s): UDF DATA
Assessment: 60.0% Coursework, 40.0% Examination
Level: 7