Intelligent Recipe Recommendation Using Machine Learning

Authors

  • S Revathi ssistant professor, Department of CSE, Erode Sengunthar Engineering College, Perundurai, Tamilnadu, India. Author
  • Selvan M Student, Department of CSE, Erode Sengunthar Engineering College, Perundurai, Tamilnadu, India. Author
  • Shivani Kumari Student, Department of CSE, Erode Sengunthar Engineering College, Perundurai, Tamilnadu, India. Author
  • Zaki Ahmad Student, Department of CSE, Erode Sengunthar Engineering College, Perundurai, Tamilnadu, India. Author

DOI:

https://doi.org/10.47392/

Keywords:

CNN, Natural Language Processing (NLP), Machine Learning

Abstract

Cooking can be seen, most of the time, as an annoying task that requires time and some essential skills. There is always a notion of ‘Our app will eliminate the monotony of cooking’ – and so it will because it offers an easier approach to discovering recipes along with the management of ingredients. This application also embodies the latest research in machine learning. It provides an easy-to-use interface to users allowing them to scan ingredients and find recipes tailored to their needs. As it stands, a Convolutional Neural Network: CNN model will support the efforts by ensuring ingredients are well positioned for cooking instruction, even for those not particularly good with proper cooking terms. Our app also uses voice commands to make out the recipes and offers the necessary steps visually, eliminating the need for writing by hand and making sure cooking becomes easier and more accessible. Even more so, our NLP capabilities allow for multiple languages, making sure users do not miss out on other cultures and the range of different cooking practices. The focus of the app is on the user experience which we believe can make the process of cooking great with a possibility of creating new dishes.

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Published

2025-05-16

How to Cite

“Intelligent Recipe Recommendation Using Machine Learning”. International Research Journal on Advanced Electronics and Computer Technology (IRJAECT), vol. 1, no. 01, May 2025, pp. 07-15, https://doi.org/10.47392/.

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