{"id":19671418,"url":"https://github.com/lasithaamarasinghe/olympic-medal-count-prediction","last_synced_at":"2026-04-10T11:02:16.449Z","repository":{"id":243218694,"uuid":"804702964","full_name":"LasithaAmarasinghe/Olympic-Medal-Count-Prediction","owner":"LasithaAmarasinghe","description":"This ML model predicts the medal count for various countries in the Olympic Games using Linear Regression.","archived":false,"fork":false,"pushed_at":"2024-06-16T06:21:32.000Z","size":318,"stargazers_count":5,"open_issues_count":0,"forks_count":1,"subscribers_count":1,"default_branch":"main","last_synced_at":"2025-02-27T04:50:13.275Z","etag":null,"topics":["jupyter-notebook","linear-regression","machine-learning","medal-count-prediction","numpy","olympics","pandas","python","sckiit-learn","seaborn"],"latest_commit_sha":null,"homepage":"","language":"Jupyter 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(1)](https://github.com/LasithaAmarasinghe/Olympic-Medal-Count-Prediction/assets/106037441/ba44c0d8-bbb5-4168-8223-dbbfe9798924)\n![file (2)](https://github.com/LasithaAmarasinghe/Olympic-Medal-Count-Prediction/assets/106037441/c66e81c7-eed4-4505-9efd-364c951644ad)\n\n\n## Overview\n\n- This project uses [**Linear Regression**](https://www.ibm.com/topics/linear-regression) to predict the medal count for various countries in the Olympic Games. \n- This repository contains all the codes and resources necessary to build and utilize the predictor.\n\n## Steps\n\n- **Data Collection**: Obtain historical Olympic medal count data for various countries.\n- **Data Preprocessing**: Clean and preprocess the data to prepare it for training.\n- **Model Training**: Train the linear regression model using the preprocessed data.\n- **Prediction**: Use the trained model to predict the upcoming Olympic Games medals.\n\n## Code\n\nYou can find the code for this project in the following files:\n\n- [Olympic Medal Count Prediction.ipynb](https://github.com/LasithaAmarasinghe/Olympic-Medal-Count-Prediction/blob/4a6fb8e1f865840f4dd589a667c3b327f050edeb/Olympic%20Medal%20Count%20Prediction.ipynb): The main project code.\n- [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.\n\n## Technologies/ Tools\n\n* Jupyter Notebook / [Google Colab](https://colab.research.google.com/)\n* Python 3.10.12\n* Python packages\n  * Pandas - `pip install pandas`\n  * Numpy - `pip install numpy`\n  * Scikit-learn - `pip install scikit-learn`\n  * Seaborn - `pip install seaborn`\n\n![Python](https://img.shields.io/badge/python-3670A0?logo=python\u0026logoColor=FFFF00)\n![Jupyter Notebook](https://img.shields.io/badge/jupyter-%23FA0F00.svg?logo=jupyter\u0026logoColor=white)\n![Pandas](https://img.shields.io/badge/pandas_-%20green?logo=pandas)\n![NumPy](https://img.shields.io/badge/numpy-%23013243.svg?logo=numpy\u0026logoColor=white)\n![scikit-learn](https://img.shields.io/badge/scikit--learn-F7931E?logo=scikit-learn\u0026logoColor=FFFFFF)\n![seaborn](https://img.shields.io/badge/seaborn_-\u0026logoColor=blue)\n\n## Data\n\nData used are from the Olympics, which was originally on [Kaggle](https://www.kaggle.com/datasets/heesoo37/120-years-of-olympic-history-athletes-and-results).\n\nYou can download the data set used in this project here:\n* [Olympic.csv](https://github.com/LasithaAmarasinghe/Olympic-Medal-Count-Prediction/blob/af2fcbcb2e5e7680be7a7a1985b3b0e90f043cc0/Olympic.csv)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flasithaamarasinghe%2Folympic-medal-count-prediction","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flasithaamarasinghe%2Folympic-medal-count-prediction","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flasithaamarasinghe%2Folympic-medal-count-prediction/lists"}