View Proposal

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Proposer

Michael Lones

Title

Applied machine learning projects

Goal

Description

This is for anyone who wants to get their teeth into a real world machine learning problem. In 4th year and MSc courses, you have the opportunity to learn the theory behind machine learning and try it out on some simple datasets. However, if you really want to get a leg up in the job market, it can be useful to show you have experience of applying machine learning and data science techniques to a real problem. If you’re interested in doing this project, please think about where you might focus before contacting me. If you’re interested in a particular problem domain, have a look which datasets are openly available. Some examples of previous projects: - Using machine learning for fraud detection in financial transactions. This used a couple of open access datasets and involved investigating data preprocessing, model selection and hyperparameter optimisation, which are three key stages of any machine learning pipeline. Explainable AI methods were then used to gain insight into how the models worked. - Using deep learning models to count fibres in images. This project focuses on developing a tool to help textiles researchers understand the ecological implications of textiles. It involved applying a range of different deep learning models to understand their applicability and limitations within this particular problem domain. - Applying machine learning to medical problems. I’ve supervised quite a few projects in this area, and they typically involve trying to come up with the best approach to solve some medical classification, regression or segmentation problem. Past examples include classifying Parkinson’s disease using drawing tablet data, using autoencoders to extract useful features from imaging data, and identifying abnormalities in images of tumours.

Resources

Background

Url

Difficulty Level

Variable

Ethical Approval

None

Number Of Students

2

Supervisor

Michael Lones

Keywords

machine learning, deep learning

Degrees

Bachelor of Science in Computer Science
Bachelor of Science in Computer Systems
Bachelor of Science in Software Development for Business (GA)
Master of Engineering in Software Engineering
Master of Science in Artificial Intelligence
Master of Science in Artificial Intelligence with SMI
Master of Science in Computer Science for Cyber Security
Master of Science in Computing (2 Years)
Master of Science in Data Science
Master of Science in Network Security
Bachelor of Science in Computer Science (Cyber Security)