FoodieHUB: Food Recipe Suggestion Using AI-ML On Web

Year : 2025 | Volume : 12 | Issue : 02 | Page : 01 07
    By

    Jaishri Shilpakar,

  • Pooja Pal,

  • Shivani Sangale,

  • Nikita Shinde,

  • Dinisha Suryawanshi,

  1. Assistant Professor, Department of Computer Engineering, Parvatibai Genba Moze College of Engineering, Pune, Maharashtra, India
  2. Student, Department of Computer Engineering, Parvatibai Genba Moze College of Engineering, Pune, Maharashtra, India
  3. Student, Department of Computer Engineering, Parvatibai Genba Moze College of Engineering, Pune, Maharashtra, India
  4. Student, Department of Computer Engineering, Parvatibai Genba Moze College of Engineering, Pune, Maharashtra, India
  5. Student, Department of Computer Engineering, Parvatibai Genba Moze College of Engineering, Pune, Maharashtra, India

Abstract

Finding a delicious recipe to cook with limited ingredients at home can be a challenging task. Many individuals struggle to prepare meals using only the ingredients they have on hand, creating uncertainty and limiting options. This project aims to develop a recipe recommendation system that utilizes machine learning algorithms to suggest recipes based on available ingredients, dietary preferences, cuisine types, cooking time, and user ratings. The project utilizes a Gradient Boosting algorithm, which is an ensemble learning technique that merges multiple weak prediction models to form a robust classifier. This approach effectively analyzes user inputs to recommend suitable recipes. The system includes both backend and frontend components to ensure a smooth user experience. The web interface offers personalized recipe recommendations, supports user authentication, and includes features such as multilingual support, recipe categories, and notifications for subscribed users. The system allows users to discover new recipes and prepare healthy meals at home while adhering to high standards of hygiene and freshness. By offering personalized recipe suggestions, the system helps users avoid eating out and promotes creativity in the kitchen, enabling them to cook the best possible dishes with their existing ingredients. Our ‘FoodieHub’ project aims to improve home cooking experiences by helping people prepare delicious meals with the resources available to them while prioritizing hygiene and healthy eating habits. 

Keywords: Machine learning, gradient boosting classifier, artificial intelligence, recipe generation, user based, item based

[This article belongs to Journal of Artificial Intelligence Research & Advances ]

How to cite this article:
Jaishri Shilpakar, Pooja Pal, Shivani Sangale, Nikita Shinde, Dinisha Suryawanshi. FoodieHUB: Food Recipe Suggestion Using AI-ML On Web. Journal of Artificial Intelligence Research & Advances. 2025; 12(02):01-07.
How to cite this URL:
Jaishri Shilpakar, Pooja Pal, Shivani Sangale, Nikita Shinde, Dinisha Suryawanshi. FoodieHUB: Food Recipe Suggestion Using AI-ML On Web. Journal of Artificial Intelligence Research & Advances. 2025; 12(02):01-07. Available from: https://journals.stmjournals.com/joaira/article=2025/view=208044


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Regular Issue Subscription Review Article
Volume 12
Issue 02
Received 25/09/2024
Accepted 28/03/2025
Published 16/04/2025
Publication Time 203 Days
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