
Developed an AI-powered allergen detection API for the SafeBite_Infosys_Internship_Oct2024 repository, delivering a foundational service for automated allergen screening in food products. The solution was implemented as a Flask application in Python, utilizing a pre-trained machine learning model and encoder loaded via Joblib to perform inference on incoming product data. A single commit introduced the core API functionality, exposing a /predict endpoint that accepts POST requests and returns JSON responses indicating detected allergens. The work established a clear input and output contract, enabling downstream integration and testing, and demonstrated proficiency in API development, data science, and machine learning workflows.
November 2024 monthly summary for SafeBite project (AabidMK/SafeBite_Infosys_Internship_Oct2024). Delivered an AI-powered allergen detection API as a Flask service that loads a pre-trained model and encoder to predict allergen presence. Exposed a /predict endpoint accepting POST requests with product details and returning a JSON response indicating detected allergens. This work lays the foundation for automated allergen screening and downstream integrations.
November 2024 monthly summary for SafeBite project (AabidMK/SafeBite_Infosys_Internship_Oct2024). Delivered an AI-powered allergen detection API as a Flask service that loads a pre-trained model and encoder to predict allergen presence. Exposed a /predict endpoint accepting POST requests with product details and returning a JSON response indicating detected allergens. This work lays the foundation for automated allergen screening and downstream integrations.

Overview of all repositories you've contributed to across your timeline