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🥗 Food Allergy Detection System
Overview
Engineered a comprehensive food safety system designed to identify hidden allergens and suggest safe meal alternatives. Unlike simple barcode scanners, this system employs NLP for ingredient standardization and utilizes multiple ML classifiers (Naive Bayes, Logistic Regression, and KNN) to analyze complex recipe compositions. Architected with a focus on high-fidelity detection, it addresses cross-contamination risks and provides user-specific allergen profiling for personalized meal recommendations.
Tech Stack
PythonNLPScikit-learnData ProcessingMachine Learning
Key Features
- ▹🧠 Integrated multi-classifier models (KNN, LogReg, Naive Bayes) for allergen identification
- ▹📝 Developed NLP pipelines for ingredient standardization and text-based recipe analysis
- ▹🛡️ Engineered safety logic to detect hidden allergens and cross-contamination risks
- ▹👤 Built user-centric profiling for personalized, safe-meal suggestions