Machine Learning explores how machines can learn from existing data to provide stochastic systems that perform tasks based on patterns and inference. The module first introduces what machine learning is, and then examines different approaches to machine learning, including decision trees and neural networks. The main body of the module focuses on building learning systems from existing data sets, as well as evaluating the performance of the systems developed. Finally, the module examines the use of machine learning in data mining, the ethical concerns related to machine learning, and how biased data sets can lead to biased systems.

Machine Learning focuses on tools, algorithms, and libraries that can be applied to data sets to build systems that can perform tasks in an intelligent manner. Students will work with a variety of tools based on the type of technique being explored that week. Students will work in programming languages best suited for the tool being used.

Machine Learning provides the capstone to the Algorithms and Artificial Intelligence theme within Computer Science. The aim is for students to have fluency in the modern tools used in a variety of industries to perform automation tasks. Students will also understand the ethical concerns of using such systems. The module builds on the basic problem-space searching techniques in Artificial Intelligence by exploring learning techniques that enable a more general intelligence approach to be applied to narrow intelligence problems.

*Course content subject to change