Financial machine learning

This unit explores the application of machine learning techniques in financial contexts, emphasising practical implementation using Python. Beginning with foundational concepts in statistical learning, the unit progresses through key supervised learning methods such as linear regression, classification, and tree-based models, before introducing unsupervised learning and deep learning techniques. Special attention is given to model evaluation, regularisation, and cross-validation. The unit culminates in advanced topics including natural language processing (NLP) in finance. Through interactive seminars and hands-on assessments, you will develop the skills to build, assess, and apply machine learning models to real-world financial problems.