This project is a part of the Machine Learning Track at the 1000ML Engineer Initiative and aims to predict football player transfer values using gradient-boosting algorithms.
The project utilizes a dataset containing historical football transfer records and player attributes. By analyzing the dataset,.
The project builds a machine learning model to predict player transfer values, which can help football clubs to make informed decisions while buying and selling players.
The dataset can be found at the following link: Summer22_FootballTransfers.csv
To use this project, you will need to install the following packages:
- pandas
- numpy
- scikit-learn
- xgboost
This project was developed as a part of the 1000ML initiative. The dataset used in this project was collected and made available by Eng. Hisham Asem