Merger Ideation

[DavidVasilev1]

Creating the Project

In this new project we are going to merge the perceptron and stock LSTM AI to create a more robust web application that demonstrates the use cases of AI across a broader range of tasks.

Coming up with the idea

To create our idea, we looked at one another's ideation to see if there were any commonalities in between them.
LSTM Ideation: Employing an LSTM to predict the trends of a particular stock ticker. Look at data in the form of time series to make accurate regression models that predict where the data ends up.
Memory ASL Game Ideation: Employs the use of a simple forward-feeding perceptron to complete complicated tasks. Passing data in the form of image data that can be used to identify certain patterns amongst the image.

Agile Methodology

We will be using the agile methodology with whole group meetings during tutorial and working individually on our parts with online collaboration most of the time.

Sprint Planning Meetings:

The team begins each sprint with a sprint planning meeting, led by the Scrum Masters. During this meeting, the team discusses and agrees upon the scope of work for the upcoming sprint. Tasks are assigned based on priorities, and estimates are provided for each user story or task.

Daily Stand-up Meetings Within Periods:

Daily stand-up meetings are conducted to ensure everyone is on the same page. Each team member, including Alex as the Scrum Master, Ethan, David, Adi, Rohin, and James, provides a brief update on their progress, plans for the day, and any obstacles they are facing within their period group and from there they will report their updates to the project in the team slack/discord to track progress. These meetings promote transparency, collaboration, and quick problem resolution.

Bi-weekly Sprint Reviews:

At the end of each sprint, the team holds a sprint review to demonstrate the completed work to stakeholders, usually done within tutorial or within during the weekends over discord. This allows for feedback and validation of the delivered features. The team, led by Alex, discusses what went well, challenges faced, and improvements for the next sprint.

Retrospective Meetings:

Following the sprint review, the team conducts a retrospective meeting to reflect on the sprint. Led by the Scrum Master, the team discusses what worked, what didn't, and identifies areas for improvement. This will be done during the tutorial and discord meetings twice a week. This continuous feedback loop helps enhance team performance and the Agile process.

Collaborative Development:

Team members (Ethan, David, Adi, Rohin, James) collaborate closely on both frontend and backend development tasks. Alex will also aid in the frontend and backend as necessary, however it will mostly be within the backend. Pair programming, where two developers work together on the same code, may be utilized to enhance code quality and knowledge sharing.

Specialized Contributions:

Each team member brings unique skills to the project. For example, Ethan and Rohin focus on neural network development with the held of Alex, Adi specializes in authentication, and James is dedicated to frontend styling. This specialization ensures a comprehensive approach to the project's diverse requirements.

Adaptability to Change:

The Agile methodology emphasizes adaptability to changing requirements. If the team encounters new insights or priorities during the development process, they can easily adjust their plans in response to feedback from stakeholders or changes in project priorities.

Meetings

Weekly Tutorial Meetings:

Frequency: Once a week
Day/Time: During the tutorial slot
Purpose: This meeting serves as the primary weekly check-in where the team, including Scrum Master Alex, Ethan, David, Adi, Rohin, and James, discusses progress, plans, and any potential challenges. It's an opportunity to align priorities and set goals for the upcoming week.

Weekend Discord Meetings:

Frequency: Once a week
Day/Time: Over the weekend (Choose a specific day and time convenient for all team members)
Platform: Discord
Purpose: This meeting provides a more relaxed setting to discuss ongoing work, share updates, and address any questions or concerns. It allows for a more informal collaboration and fosters a sense of camaraderie within the team.

Ad Hoc Issue Resolution Meetings:

Frequency: As needed
Initiation: Meetings are triggered when specific issues arise in the code or when there's a need for urgent collaboration.
Platform: Discord or other preferred communication channels
Purpose: These ad hoc meetings are focused on resolving immediate challenges in the code. Team members collaborate to troubleshoot and find solutions efficiently. Once the issue is resolved, the team may return to the regular meeting schedule.

Roles

Alex (Scrum Master):

• Role: Scrum Master
• Description: Responsible for overseeing the Agile process, facilitating communication, and ensuring the team adheres to Scrum practices. Also contributes to both frontend and backend development, with a primary focus on implementing the neural network for stock prediction in the backend.

Ethan:

• Role: Frontend and Backend Developer
• Description: Works on integrating frontend and backend components, with a specific focus on connecting the neural network for stock prediction. Collaborates with other team members to ensure seamless interaction between different layers of the application.

David:

• Role: Frontend and Backend Developer
• Description: Specializes in creating the admin page and contributes to frontend styling and layouts. Focuses on enhancing the user interface and experience while also participating in backend development tasks.

Adi:

• Role: Frontend and Backend Developer
• Description: Primarily involved in developing the admin page and implementing login authentication using JWTs between the frontend and backend. Also contributes to AI development tasks, supporting the team with expertise in this area.

Rohin:

• Role: Frontend and Backend Developer
• Description: Assists in backend development, particularly in working on the neural network. Also contributes to the development of the admin panel, ensuring a well-rounded skill set in both frontend and backend tasks.

James:

• Role: Frontend and Backend Developer
• Description: Concentrates on frontend styling, organization, and overall user interface improvements. Additionally, works on creating and managing the backend user database to support the application's functionality.

Stock AI Predictions

Backend: Java Spring

Purpose

The Java Spring backend in our Stock AI Predictions project serves as the brain of the AI system, managing data processing, decision-making, data prediction, and communication.

Architecture

1. Spring Framework: Employed for building a scalable and modular backend, ensuring efficient control and coordination of neural networks. Will attempt to integrate a deeplearning4j LSTM network into Spring.
2. RESTful API: Facilitates communication between the AI backend and user interfaces on our frontend, enabling seamless data exchange.
3. Data processing and cleaning: Incorporates modules for processing data from CSV or XML files. Some cells within the files may have blank, null, or NaN values. We must create sufficient filters that allow us to ensure that our data is filtered and cleaned for our model to work on. Possible ideas are to use Python scripts along with pandas library for greatest simplicity.

Key Features

• Stock Predictions: Uses LSTM along with other RNN implementations to see how past trends across stock tickers could be used to predict future values in the stock market. This would require a lot of data to be accurate and reliable.
• Model training and learning: The model needs certain learning, optimization, and parameters to enable the best form of learning. The group will also research vector calculus and stochastic gradient descent algorithms to learn how neural networks learn.
• Real-time Learning: Enables quick responses to external stimuli and user commands. As the stock market progresses, perhaps the model should learn on its own

Frontend: Jekyll

Purpose

This Jekyll interface works as a UI for the users to see the stock predictions that the AI outputs and for users to use this data to buy stocks that are predicted to perform the best.

Architecture

1. Static Site Generator: Jekyll simplifies frontend development, generating static HTML files for quick rendering on active sites.
2. Responsive Design: Ensures the interface adapts to various computer displays and phone screens.
3. Status Updates: Displays real-time information about the stock predictions that the user follows and other similar stocks.

Key Features

• Fake Money: Allows the user to invest "money" based on the stock predictions and this will allow the users to test the program.
• Stock Page: Contains all of the stocks that the user follows and allows the user to add and remove stocks that they want to invest in.
• Organizations: People are going to be able to create organizations with other users to create groups in which they can compare their earnings and "compete".

Integration

Seamless Robotic Interaction

The Java Spring backend and Jekyll frontend seamlessly interact through RESTful APIs, enabling real-time data display in the stock prediction model.

Continuous Prediction Improvement

The modular architecture facilitates updates and improvements, ensuring the stock prediction evolves to meet changing data in the world of stocks and demands.

Conclusion

This stock prediction program, powered by a Java Spring and Jekyll frontend, integrates artificial intelligence and visual representations into a prediction system aiding traders in choosing the best stocks for investing. The combination of model training and real time learning will allow the AI to always be updated with current data that will integrate visual representations for users to see.