Machine Learning

About

Much of modern machine learning rests upon a range of mathematical methods, and many introductory machine learning modules seek to introduce algorithms before ensuring the link with these methods is made.

This module aims to offer you an introduction to traditional machine learning in a rigorous mathematical fashion.

Assuming familiarity with key results in linear algebra, differential calculus, probability and statistics, the module introduces major areas of traditional machine learning and covers the key tools (and theorems) within these areas, illustrating them with practical examples.

The module is delivered through a mixture of lectures and classes, involving traditional lecture delivery, interactive notebooks and problem sets.

Week one
Continuous Maths Recap
Regression
Classification

Week two
Model Selection
Kernel Methods
Support Vector Machine
Dimensionality Reduction

Week three
Clustering
Neural Networks

Course leader

Dr Dariush Hosseini

Course aim

This module aims to:

- Introduce you to the fundamental concepts of machine learning using the language of continuous mathematics.
- Introduce practical tools for the application of machine learning

Fee info