Enhanced Dynamic Model Retraining and API Integration

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Enhanced Dynamic Model Retraining and API Integration

  • Day: 2024-04-13
  • Time: 21:40 to 22:30
  • Project: Dev
  • Workspace: WP 2: Operational
  • Status: Completed
  • Priority: MEDIUM
  • Assignee: Matías Nehuen Iglesias
  • Tags: Flask, Javascript, Machine Learning, API, Data Visualization

Description

Session Goal

The session aimed to enhance dynamic model retraining, improve [[data visualization]], and integrate robust API endpoints in a web application for predicting diamond prices.

Key Activities

  • Organized Git Commits: Structured commits by functionality and ensured meaningful commit messages for better version control.
  • Technical Overview: Reviewed the architecture and session plan for a diamond price prediction application using Flask, Pandas, and Scikit-Learn.
  • Development Preparation: Focused on UI enhancements, testing, and documentation for the development session.
  • Model Optimization: Optimized dynamic model retraining and visualization strategies, emphasizing real-time updates and data handling.
  • API and Frontend Development: Created a fetchModels function and Flask API endpoint for dynamic [[data visualization]], ensuring integration between frontend JavaScript and backend Flask.
  • Error Handling: Resolved JavaScript error Uncaught TypeError: document.getElementById(...) is null by ensuring element existence and managing script loading order.
  • Flask Endpoint Fix: Adjusted /[[api]]/plot-data endpoint to include model_name parameter, updating frontend JavaScript accordingly.

Achievements

Pending Tasks

  • Further testing and validation of the integrated features in a production environment.
  • Continuous monitoring and optimization of model retraining strategies.

Evidence

  • source_file=2024-04-13.sessions.jsonl, line_number=2, event_count=0, session_id=ef3f8fc6d7e2e2eda18b66bde2b3f7d6a0900d6825f67583a6e3f32b5a2d629a
  • event_ids: []

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