Football Players Value Prediction using Classification Method

Project Goal: This project was created to obtain predictive value in football players using Decision Tree and Random Forest algorithms.

Task: Performed data preparation and Exploratory Data Analysis on FIFA 21 Football Player Data, and built classification models using Decision Tree and Random Forest algorithms. Results showed that Decision Tree outperformed Random Forest with an accuracy of 86.63%.

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