🚀 Stoquette Datathon Project
Welcome to Stoquette, a revolutionary datathon project hosted at Georgia Tech where we leveraged the power of MongoDB, Python, HTML, CSS, and JS to craft an innovative website that redefines the way we interact with stock information.
📈 Advanced Data Analysis: Utilized comprehensive datasets to analyze market volatility, highs, lows, and other critical financial indicators.
🤖 Gen-AI Integration: Implemented cutting-edge Generative Artificial Intelligence to enhance predictive modeling and decision-making processes.
📰 Sentiment Analysis: Employed sentiment analysis on recent financial articles, providing valuable insights into market sentiments and trends.
- MongoDB: A database for efficient data storage and retrieval.
- Python: The primary programming language for data manipulation, analysis, and backend development.
- HTML & CSS: Designed an intuitive and user-friendly frontend interface for seamless user experience.
- JavaScript: Implemented dynamic functionalities to enhance user interactivity.
Our mission was to simplify stock trading by providing users with a comprehensive and user-friendly platform that amalgamates complex financial data into easily digestible insights. The combination of data analytics, artificial intelligence, and sentiment analysis aimed to empower users in making informed investment decisions.
Download the files above and go live with the index.html file. We are currently working on deploying our project into a domain for easier use.
A heartfelt thank you to the Georgia Tech community for organizing and participating in this datathon. This project wouldn't have been possible without the collaborative efforts of our dedicated team.
Feel free to explore the GitHub repository for the source code, documentation, and additional insights.
Let's simplify the stock market together! 📊🚀