
Worked on the Intelligent-Advisor-Sem-4/backend repository to establish a robust backend foundation and enhance predictive capabilities. Over two months, built PostgreSQL-backed persistence with secure environment variable management, reducing deployment friction and supporting future data-driven features. Refactored connection logic for improved portability and added tests to catch misconfigurations early. Focus then shifted to expanding the Prediction API, introducing 7-day forecast endpoints, a model details endpoint, and migrating data-heavy routes to POST for better throughput. Comprehensive unit tests were developed to ensure reliability. The work leveraged Python, FastAPI, SQLAlchemy, and Pydantic, emphasizing maintainability, scalability, and secure database interaction throughout.
May 2025 backend focus: Strengthen the Prediction API for reliable, scalable forecasts and expand test coverage to reduce defects, enabling faster, data-driven decisions for customers.
May 2025 backend focus: Strengthen the Prediction API for reliable, scalable forecasts and expand test coverage to reduce defects, enabling faster, data-driven decisions for customers.
April 2025 monthly summary for Intelligent-Advisor-Sem-4/backend: Focused on establishing a solid data layer foundation by enabling PostgreSQL-backed persistence and secure configuration management. This work reduces deployment friction, supports data-driven features, and improves reliability for future work.
April 2025 monthly summary for Intelligent-Advisor-Sem-4/backend: Focused on establishing a solid data layer foundation by enabling PostgreSQL-backed persistence and secure configuration management. This work reduces deployment friction, supports data-driven features, and improves reliability for future work.

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