Principles of Machine Learning

Module code: ECS7020P

Credits: 15.0
Semester: SEM1

Contact: Dr Jesus Requena-Carrion

Principles of Machine Learning covers the fundamental concepts, methodology and practical tools necessary to understand, build and assess data-driven models to describe real-world systems and predict their behaviour. We will follow the standard machine learning taxonomy to organise problems and techniques into well-defined families (supervised and unsupervised learning) and subfamilies. We will pay particular attention to the methodology that we need to use to avoid and identify common pitfalls. State-of-the-art models and the latest developments on model deployment will be discussed.

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