Browse Hierarchy ECS663U: Principles of Machine Learning

Machine learning lies in the intersection between statistics and computer science and can be found in many fields, from science and high-tech to applied areas such as retail and finance. Its main goal is to develop data-driven models to understand and predict the behaviour of real-world systems. Not surprisingly, machine learning skills are in high demand. This module is an introduction to the principles of machine learning. The main concepts, approaches and tools necessary to develop and evaluate machine learning solutions will be covered following a hands-on approach. This exposure will give you a solid understanding of machine learning. Furthermore, it will allow you to go ahead and independently develop your machine learning skills further and to critically analyse any future developments in the field of data science. This module covers the following key concepts and themes: Machine learning fundamentals: Introduction to machine learning Methodology I and II Supervised problems and techniques: Regression Classification Unsupervised problems and techniques: Structure analysis Density Estimation Recent Topics: Modern neural networks and deep learning Deployment