ProtoSim: Varient data generation for training AI models (Sophisticated ML algos)

Description:

ProtoSim is a project designed to facilitate automated A/B testing for AI model prototypes. The project workflow involves:

1. Data Generation: Creates random data for two app variations.
2. Data Analysis: Processes the generated data through an analysis pipeline, producing insights and visualizations.
3. Data Storage: Organizes analyzed data in a PostgreSQL database.

Key Features:

• Data Insights: Provides detailed analysis and visual representation of results.
• Efficient Storage: Manages data and visualizations efficiently using PostgreSQL and local file storage.

This project demonstrates advanced skills in data generation, analysis, visualization, and database management, leveraging Python and PostgreSQL for robust performance and organization.

GitHub Repository