Mirabito - Ata Gunaydin; Elif Yildrim; Ozguven Salih; Same Genc;

From CS486wiki
Jump to navigationJump to search

Week 1 09/09/2025

Attendance: Samet GENC, Elif YILDIRIM, Ata GUNAYDIN, Salih OZGUVEN

Summary: This week, we held our initial project meeting and outlined the scope of the two interconnected projects: the AI Loyalty Engine and the Data Infrastructure Modeling. We reviewed technical requirements, development tools, and environment setup instructions, including Node.js, Angular, and C#. Additionally, we discussed laptop preferences and extension configurations to ensure a smooth development workflow across platforms.

Accomplishments:

  • Defined project responsibilities: AI Loyalty Engine vs. Data Infrastructure Modeling.
  • Reviewed system architecture and collaboration needs between both groups.
  • Shared setup instructions for Node.js, Angular CLI, and C#.
  • Established development environment recommendations for Windows and Mac (Visual Studio / VS Code).

To-Do:

  • Install required tools (Node.js, Angular CLI, VS/VS Code with extensions).
  • Coordinate regular check-ins between both project teams.


Week 2 & Week 3 09/16/2025

Attendance: Samet GENC, Elif YILDIRIM, Ata GUNAYDIN, Salih OZGUVEN

Summary: This week, we focused on reviewing the provided datasets and understanding their features. We examined both the Customer Basket and Inventory data to explore potential correlations and identify missing elements necessary for modeling. Additionally, we analyzed the AI engine code from the repositories to gain insights into the existing implementation. Finally, we held discussions with Kaan Balta from last year’s team, who provided observations and context regarding the codebase and its structure.

Accomplishments:

  • Reviewed Customer Basket dataset and Inventory data, working to identify correlations between them.
  • Explored dataset features and clarified column definitions, missing values, and potential resolutions.
  • Investigated the AI Loyalty Engine source code and associated programs in the repositories.

To-Do:

  • Draft scope documents outlining tasks, timelines, milestones, constraints, and deliverables.
  • Propose solutions for gaps identified in the Inventory dataset.
  • Continue deep-diving into feature relationships between datasets to refine modeling strategy.
  • Begin aligning Data Infrastructure outputs with AI Loyalty Engine requirements for integration.
Retrieved from "https://www.cs.binghamton.edu/~steflik/wiki/index.php?title=Mirabito_-_Ata_Gunaydin;_Elif_Yildrim;_Ozguven_Salih;_Same_Genc;&oldid=14094"