📅 2024-04-07 — Session: Developed MLOps plan for diamond pricing app
🕒 15:50–16:40
🏷️ Labels: Mlops, Machine Learning, Diamond Pricing, Cloud Infrastructure
📂 Project: Dev
⭐ Priority: MEDIUM
Session Goal
The main objective of this session was to develop a comprehensive plan for a diamond price prediction application, focusing on MLOps, Flask application enhancements, Docker optimization, cloud infrastructure planning, and documentation best practices.
Key Activities
- Outlined the agenda for developing the diamond price prediction application, covering MLOps, Flask, Docker, and cloud technologies.
- Formulated guiding questions to direct the project planning, addressing objectives, data quality, model metrics, infrastructure, and budget.
- Provided an overview of the project, detailing objectives, current status, data sources, and security considerations.
- Developed a comprehensive MLOps strategy, covering model development, deployment, monitoring, and re-training.
- Created a 10-day MLOps workflow plan focusing on setup, model training, deployment, and documentation.
- Planned the integration of a new ‘special’ characteristic into the diamond dataset to enhance UI and model training.
Achievements
- A detailed MLOps strategy and a structured 10-day workflow plan were established, setting a clear path for the project’s execution.
- Addressed critical aspects of the project, including infrastructure, data management, and security.
Pending Tasks
- Implement the outlined MLOps strategy and 10-day workflow plan.
- Integrate the ‘special’ characteristic into the diamond dataset and update the model training processes accordingly.