Random Forest Classifier - FIFA Player Dataset

This repository contains a Jupyter Notebook that applies a Random Forest Classifier to predict characteristics or classifications of FIFA players based on their attributes. The analysis demonstrates a machine learning workflow including data preprocessing, model training, evaluation, and visualization.

File Structure

RANDOM FOREST FIFA.ipynb: Main notebook containing the data analysis, preprocessing, and application of the Random Forest Classifier on FIFA player data.

🔍 Features

Exploratory Data Analysis (EDA) of FIFA dataset

Data Cleaning and Feature Selection

Implementation of Random Forest Classification

Model Evaluation using accuracy and confusion matrix

Visualization of model performance

🛠️ Requirements

Python 3.x

Jupyter Notebook

pandas

scikit-learn

matplotlib

seaborn