This project depicts the code part of my seminar thesis about feature selection in regression tasks, where i dive deeper into the functionality of subset selection and regularization methods. The functionality lies in underlying_functions.py, while the illustrations are shown in Jupyter_Overview.ipynb. The Analysis is made using an NBA 🏀 data set, deployed here, this data set contains the playing and salary data for NBA players of the 2021/22 season. The goal of the Analysis was to detect the in game statistics, that have the best prediction power in a linear regression setting, where our target variable is the salary of a player.