FIN 688 Machine Learning for Finance
This course introduces a range of machine learning techniques and their applications in finance. Students will explore both supervised learning algorithms, such as linear models, logistic regression, support vector machines, random forests, and neural networks; and unsupervised learning methods including principal component analysis and cluster analysis. Students will apply machine learning techniques to financial tasks such as credit risk analysis, portfolio management, and market prediction. Both theories and implementations in Python are emphasized. This course is designed to equip students with the skills to leverage machine learning for solving financial challenges and improving decision-making processes in the finance industry.
Credits
4
Offered
Fall and Spring