https://github.com/lasithaamarasinghe/olympic-medal-count-prediction

This ML model predicts the medal count for various countries in the Olympic Games using Linear Regression.
https://github.com/lasithaamarasinghe/olympic-medal-count-prediction

jupyter-notebook linear-regression machine-learning medal-count-prediction numpy olympics pandas python sckiit-learn seaborn

Last synced: about 1 month ago
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This ML model predicts the medal count for various countries in the Olympic Games using Linear Regression.

• Host: GitHub
• URL: https://github.com/lasithaamarasinghe/olympic-medal-count-prediction
• Owner: LasithaAmarasinghe
• Created: 2024-05-23T05:24:06.000Z (9 months ago)
• Default Branch: main
• Last Pushed: 2024-06-16T06:21:32.000Z (8 months ago)
• Last Synced: 2024-11-11T17:08:43.851Z (3 months ago)
• Topics: jupyter-notebook, linear-regression, machine-learning, medal-count-prediction, numpy, olympics, pandas, python, sckiit-learn, seaborn
• Language: Jupyter Notebook
• Homepage:
• Size: 311 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        
# Olympic-Medal-Count-Prediction

![file (1)](https://github.com/LasithaAmarasinghe/Olympic-Medal-Count-Prediction/assets/106037441/ba44c0d8-bbb5-4168-8223-dbbfe9798924)

![file (2)](https://github.com/LasithaAmarasinghe/Olympic-Medal-Count-Prediction/assets/106037441/c66e81c7-eed4-4505-9efd-364c951644ad)

## Overview

- This project uses [**Linear Regression**](https://www.ibm.com/topics/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](https://github.com/LasithaAmarasinghe/Olympic-Medal-Count-Prediction/blob/4a6fb8e1f865840f4dd589a667c3b327f050edeb/Olympic%20Medal%20Count%20Prediction.ipynb): The main project code.

- [Data Preparetion.ipynb](https://github.com/LasithaAmarasinghe/Olympic-Medal-Count-Prediction/blob/4a6fb8e1f865840f4dd589a667c3b327f050edeb/Data%20Prep.ipynb): The code to generate the team-level dataset from an athlete-level dataset.

## Technologies/ Tools

* Jupyter Notebook / [Google Colab](https://colab.research.google.com/)

* Python 3.10.12

* Python packages

  * Pandas - `pip install pandas`

  * Numpy - `pip install numpy`

  * Scikit-learn - `pip install scikit-learn`

  * Seaborn - `pip install seaborn`

![Python](https://img.shields.io/badge/python-3670A0?logo=python&logoColor=FFFF00)

![Jupyter Notebook](https://img.shields.io/badge/jupyter-%23FA0F00.svg?logo=jupyter&logoColor=white)

![Pandas](https://img.shields.io/badge/pandas_-%20green?logo=pandas)

![NumPy](https://img.shields.io/badge/numpy-%23013243.svg?logo=numpy&logoColor=white)

![scikit-learn](https://img.shields.io/badge/scikit--learn-F7931E?logo=scikit-learn&logoColor=FFFFFF)

![seaborn](https://img.shields.io/badge/seaborn_-&logoColor=blue)

## Data

Data used are from the Olympics, which was originally on [Kaggle](https://www.kaggle.com/datasets/heesoo37/120-years-of-olympic-history-athletes-and-results).

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

* [Olympic.csv](https://github.com/LasithaAmarasinghe/Olympic-Medal-Count-Prediction/blob/af2fcbcb2e5e7680be7a7a1985b3b0e90f043cc0/Olympic.csv)