Olympic Medal Predictions

This repository houses the final project of students at the University of Texas Data Analytics and Visualizations Bootcamp. The results of our efforts can be found here. We hope you like it! :blush: :tada:

Contributors:

Curtis Dean, Sapana Donde, Mona Elahi, Elisabeth Newman, Nikhila Rentam, Alissa Roegge

Overview

The purpose of this project is to create a website containing information about the Olympics, including an interactive page that will predict whether a person with certain biometric data, sex, and region would medal in a given event. The project is broken into 3 distinct categories. The links below contain additional information about each part of the project.

Exploratory Data Analysis and Visualizations

Contributors: Curtis Dean, Elisabeth Newman, and Alissa Roegge.

Machine Learning

Contributors: Mona Elahi, Nikhila Rentam, Alissa Roegge

Web Development and Deployment

Contributors: Curtis Dean and Sapana Donde

Credits

Tools

We leverage many tools in our project in order to accomplish our goals. Below is a list of tools/languages used in the project.

• Heroku - Used for web deployment
• HTML/CSS - Used for web development
• Python - Used for machine learning
  • Pandas, Numpy, Scipy, Scikit-learn, Imbalanced-learn, Statsmodels, Matplotlib
• R - Used for EDA
  • Dplyr, GGplot, Stringr, etc. Basically the entire Tidyverse suite of packages
• Tableau - Used for EDA/Storytelling

Dataset

The dataset that we use originally came from Kaggle and can be found here.