Recipe Recommendation System

Author(s)	Abhishek Pandey, Abhishek gupta, Roshini Varma, Bhanu tekwani
Country	India
Abstract	In the era of rapid urbanization and busy lifestyles, individuals often face the challenge of preparing meals with the limited ingredients available at home. To address this issue, we present a sophisticated Recipe Recommendation System based on ingredients, leveraging the power of Python, flask, and MongoDB. The proposed system aims to revolutionize the way people approach cooking by providing personalized and efficient recipe suggestions tailored to the ingredients users already have. The proposed system employs advanced algorithms to match user-provided ingredients with a vast and diverse recipe database. By considering factors such as ingredient availability, the system generates real-time, tailored recipe recommendations. The integration of machine learning techniques ensures accurate ingredient matching and enhances the system's ability to adapt to individual users' tastes and needs
Keywords	: Recipe Recommendation System Ingredients, Advance Algorithms, Real-time Recommendations. I. INTRO
Field	Engineering
Published In	Volume 6, Issue 2, March-April 2024
Published On	2024-04-29
Cite This	Recipe Recommendation System - Abhishek Pandey, Abhishek gupta, Roshini Varma, Bhanu tekwani - IJFMR Volume 6, Issue 2, March-April 2024. DOI 10.36948/ijfmr.2024.v06i02.18285
DOI	https://doi.org/10.36948/ijfmr.2024.v06i02.18285
Short DOI	https://doi.org/gtsnwn

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