Geek-Olympic Hackathon Project

Introduction

Welcome to our Geek-Olympic Hackathon project! This submission aims to enhance the Olympics experience for users and organizers through a web-based application that offers various exciting features. We have utilized the provided Olympic dataset along with other data from the internet to create a feature-rich platform for Olympic enthusiasts.

Project Overview

Our web-based application, Geek-Olympic WebApp, provides users with an interactive interface to stream various Olympic events and engage with them in a fun manner. It incorporates the following key features:

1. Live Streaming & Interaction: We have integrated Vimeo, a live-streaming platform, to broadcast ongoing events. Users can interact with the live stream through comments, like events, and view multiple ongoing events simultaneously.

2. Predictive Analysis: Our system includes a prediction model based on Sklearn's Gradient Boosting Classifier. This model predicts the likelihood of an athlete winning a medal based on various attributes, such as age, height, weight, gender, sport, country, and the season of the Olympics. While the model's accuracy is approximately 45%, it provides valuable insights into athletes' performances.

3. Sentiment Analyzer: To gauge public sentiment during the event, we have implemented a sentiment analysis model based on Hugging Face's pretrained roBERTa model (cardiffnlp/twitter-roberta-base-sentiment). The sentiment analyzer processes tweets related to the Olympics, providing an overall accuracy of around 67% and an average f1 score of 0.635.

4. Interactive Charts: We have utilized various plotting types, including pie charts, bar plots, radar plots, line plots, and doughnut plots, to provide users with a better understanding of the Olympics data and enhance their overall experience.

5. Authentication & Data Protection: To ensure a smooth and secure user experience, we have integrated Auth0 for authentication, authorization, and data protection of our users.

6. Chat Bot Assistance: Our platform features a chatbot powered by the GPT-3 model to assist users with their queries and provide helpful information.

Tech Stack

The project is built using the following technologies:

• Backend: Python with Fast API as the web framework
• Database: CockroachDB (Serverless Cloud Instance)
• Frontend: React for the user interface
• Live Streaming Platform: Vimeo for broadcasting events
• Authentication: Auth0 for secure user access
• Prediction Model: Sklearn's Gradient Boosting Classifier
• Sentiment Analysis Model: Hugging Face's pretrained roBERTa model (cardiffnlp/twitter-roberta-base-sentiment)

Environment Files Setup

The steps to add the environment files and the root.crt file are as follows:

• api/auth/.env: Create a file named .env inside the api/auth/ directory. Add the necessary configuration variables for the API and Auth0 in this file.

• streaming/.env: Create a file named .env inside the streaming/ directory. Add the required configurations for the Vimeo live streaming platform in this file.

• .env: Create a file named .env in the project's root directory. Add the DB_USERNAME & PASSWORD.

• models/server.env: Create a file named server.env inside the models/ directory. Add the specific environment variables required for the predictive and sentiment analysis models.

• CockroachDB Signing Key (root.crt): Place the root.crt file inside the certs/ directory. This ensures secure communication with the CockroachDB.

• Please ensure that you add all the necessary configurations to these environment files to avoid any issues while running the Geek-Olympic WebApp.

Achievements

Throughout the development process, we achieved notable results:

• The predictive model using Sklearn's Gradient Boosting Classifier achieved an accuracy of approximately 45% with both an f1-score and precision score of 0.53.

• The sentiment analysis model using roBERTa achieved an overall accuracy of around 67%, an average f1 score of 0.635, an average recall score of 0.652, and an average precision score of 0.671.

Video

Geek.A.Thon.-.Olympus.mp4

ScreenShots

For more screenshots, click here.

Run

• Backend

pip install -r ./requirements.txt
py main.py

• Frontend

npm i
npm start

Acknowledgments

We would like to express our gratitude to the organizers of the Geek-Olympic Hackathon for providing us with this opportunity to work on such an exciting project.

Thank you for exploring our Geek-Olympic WebApp! We hope you enjoy the enhanced Olympics experience it provides. Happy hacking and happy Olympics! 🏅🎉