The goal is to predict football players’ market values based on their statistics. My teammate and I developed a user-friendly GUI for scouts to access clear and precise information. We have used XGBoost Linear Regression kNN Decision Tree and Random Forest for predictions. R-Squarred Error N-Fold Accuracy and Mean Squarred Error was used for improving models and evaluating results.
Technologies used in the project:
- Python
- Pandas
- Numpy
- Sklearn