Abstract
Team Name
Data Wizards
Timeline
Fall 2023 – Spring 2024
Students
- Ishan Poudel
- Huy Nguyen
- Joey Hussain
- Ansh Sharma
- Maulik Sehgal
- Muhammad Muawiz Farooqi
Background
TradeMinds is a venture in the realm of financial technology, set to revolutionize the field of stock market trading with community shared machine learning algorithms. The platform is a comprehensive ecosystem designed to empower users in their stock market endeavors. It achieves this through a unique blend of features, including data processing, intricate model evaluation, and an interface that allows for collaboration.
To achieve our goal, we worked with multiple applications including Python, React, Flask, Amazon Web Services, Cloudinary, and Vercel to build our product.
Project Requirements
Upload System: The user can upload a model and the backend will calculate the average MSE for the previous day, week, month, and year.
Like System: Allow the user to like and therefore save any model they are interested in keeping an eye on for the future.
Community Feedback: Allows the user to leave comments as well as like other comments on any models that they are viewing.
Profile Page: Allow the user to view their liked models, and their own models that have created to have ease of access to the models they care about the most.
Settings Page: Allow the user to change their password and profile picture for the web application.
Model Visualization: On the home page dashboard and on the model pages. We provide visualization on how the model has performed on the stock market data.
Backend Authorization: Create a secure authorization system for registering and logging to protect user data.
About Page: Create an in depth about page for the user to get to know the product and the team behind it.
System Overview
Presentation/UI Layer
This layer consists of three main sections in the platform the Profile Page in which users can see the models they have created and liked, the Home Section which includes the top performing models and visualizations for each models, and the Login/Registration page where users can create an account and login into the website.
Computational Layer
This layer is responsible for ranking our models in terms of best MSE values as well as likeability by the user base. It also includes calculating the values based off our backend data from our API and using it to see how well the model uploaded performs. Lastly it includes cleaning up the data from our API into nicer outputs for seamless visualization.
Backend Layer
This layer is responsible for handling all user data and model data as well as fetching the data from the stock API. This layer involves building out the database and providing user endpoints.
Results
Dashboard: Top Performing Models chart
Model Page
Model Submission
Future Work
In conclusion, the TradeMinds team has implemented a platform that allows for the user to upload models, view model visualizations, provide feedbacks as well as like models, and secure user authorization information. We believe that for the future work we can implement new ideas, as well as improve upon the current system. These ideas include having a more robust model upload feature that does not have as many constraints on the way the models needs to be uploaded and adding additional visualization for every model on their respective model page so that the user’s have more visual aids to improve knowledge and information about each model.
Project Files
System Requirements Specification
Architectural Design Specification
Back-end code documentation (Download the folder and use index.html to view full documentation)
Front-end code documentation (Download the folder and use index.html to view full documentation)
References
“Installing Next Cloudinary.” Cloudinary, 2024, https://next.cloudinary.dev/installation
”Vercel Documentation.” Vercel, 2024, https://vercel.com/docs
”Getting Started.” NextJS, 2024, https://nextjs.org/docs/getting-started/installation
“Create user interfaces from components.” React, 2024, https://react.dev/
“MySQL 8.0 Reference Manual.” MySQL, Oracle, 2024, https://dev.mysql.com/doc/refman/8.0/en/
“Welcome to Flask.” Flask, Pallets Projects, 2024, https://flask.palletsprojects.com/en/3.0.x/
“Amazon EC2 Instances.” Amazon Web Services, 2024, https://aws.amazon.com/ec2/instance-types/
