Olympic-Medal-Count-Prediction

Overview

• This project uses Linear Regression to predict the medal count for various countries in the Olympic Games.
• This repository contains all the codes and resources necessary to build and utilize the predictor.

Steps

• Data Collection: Obtain historical Olympic medal count data for various countries.
• Data Preprocessing: Clean and preprocess the data to prepare it for training.
• Model Training: Train the linear regression model using the preprocessed data.
• Prediction: Use the trained model to predict the upcoming Olympic Games medals.

Code

You can find the code for this project in the following files:

• Olympic Medal Count Prediction.ipynb: The main project code.
• Data Preparetion.ipynb: The code to generate the team-level dataset from an athlete-level dataset.

Technologies/ Tools

• Jupyter Notebook / Google Colab
• Python 3.10.12
• Python packages
  • Pandas - pip install pandas
  • Numpy - pip install numpy
  • Scikit-learn - pip install scikit-learn
  • Seaborn - pip install seaborn

Data

Data used are from the Olympics, which was originally on Kaggle.

You can download the data set used in this project here:

• Olympic.csv