This repository contains the codes (For the assignments) for the "AI in Finance" course taught by prof. Ing. Štefan Lyócsa, PhD. The code covers key topics of machine learning with a focus on case studies in financial markets, credit and profit scoring, hedonic price models for real estate and used cars.
The codes covers a range of topics, including:
- Data pre-processing
- Unsupervised learning methods
- Predictive modeling using OLS, LASSO, RIDGE, EN, Complete Subset Regressions, Logistic regression, and Random Forest
- Basic principles of Gradient Boosting, Support Vector Machines, and other methods
- Handling data-snooping bias, hyper-parameter tuning, bagging and boosting, and ensemble learning.
- Basic knowledge of R programming
- R and RStudio installed on your computer
This course is licensed under the MIT License. Feel free to use, distribute, and modify the course materials for your own purposes.