Dr Jesus Requena

Teaching

Principles of Machine Learning (Postgraduate)

This module  covers the fundamental concepts, methodology and practical tools necessary to understand, build and assess data-driven models that 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 supervised learning) and subfamilies. We will pay particular attention to the methodology that we need to use to identify and avoid common pitfalls and we will reflect on professional aspects of machine learning.

At the end of the module students will be able to apply the machine learning methodology to build and rigorously evaluate machine learning systems. Furthermore, students will be able to independently learn and apply new machine learning techniques, and to critically analyse reports on machine learning applications and advances.

Research