Presentation: #

Weekly Progress Report: #

In the final 6 week of our project, we achieved significant milestones in the development and integration of the ML, Backend, and Frontend components.

ML Component #

Accomplishments: #

• Conducted the final testing of the model’s training environment.
• Finalized and prepared two ML models based on reinforcement learning techniques for demonstration.
• Implemented real-time cryptocurrency price prediction.
• Completed the README and organized the GitHub repository.
• Performed the final iteration with the Backend component via the ZeroMQ asynchronous library.

Next Week’s Key Tasks: #

• Prepare a presentation segment explaining the ideas and techniques behind the ML component.
• Set up infrastructure to move the project from a local presentation machine to a remote server.
• Collect real-time system performance statistics for demo days.
• Conduct a review session to discuss the achievements and challenges of the project.

Backend Component #

Accomplishments: #

• Integrated a new Momentum Strategy trading algorithm into the automated system.
• Completed the final iteration with the ML component via the ZeroMQ asynchronous library.
• Final testing of the trade algorithms was conducted, and charts were generated to interpret predictions.
• Completed the README and organized the GitHub repository.
• Implemented real-time cryptocurrency price prediction.

Next Week’s Key Tasks: #

• Prepare a presentation segment explaining the ideas and techniques behind the Backend (Trade algorithms) component.
• Conduct a review session to discuss the achievements and challenges of the project.
• Collect real-time system performance statistics for demo days.
• Redesign the database logging to align with the current frontend design.

Frontend & Design Components #

Accomplishments: #

• Simplified the Figma design model to speed up the web interface development.
• Implemented the home page and added dynamic graphics.
• Configured and connected to the database with logs.
• Created an interface visualizing the decision engine’s operation based on general voting ML models and trade algorithms.

Next Week’s Key Tasks: #

• Finalize the development of the dynamic dashboard.
• Begin developing device adaptations.
• Add metrics and visualizations to enhance the interpretation of the decision engine.

Challenges & Solutions #

1. Challenge: Simplifying the current UX/UI design due to limited web interface development experience.

   Solution: After presenting the first MVP, we plan to expand the team and hire qualified personnel.

2. Challenge: Inability to demo the project remotely, requiring local device demonstration.

   Solution: We will focus on optimizing the product for the presentation while exploring remote and autonomous system setup options for hosting the product.

General conclusion #

The past six weeks have been an intensive and productive period of development, during which we achieved significant progress across all project components. Our team successfully finalized and integrated the ML, Backend, and Frontend elements, ensuring a robust and cohesive system. The challenges we faced were met with effective solutions, paving the way for a strong foundation as we transition to the presentation stage.

This journey has not only strengthened our technical skills but also highlighted the importance of teamwork and adaptability. We deeply appreciate the guidance and support from our mentors, whose insights were invaluable in navigating the complexities of this project. The course itself provided a comprehensive framework that was crucial in shaping our approach and achieving our goals.

Overall, this project has been a rewarding experience, and we are excited to showcase our work and continue building on this solid groundwork in the future.