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Stream/Area:
-
Subject:
-
Paper ID:
10.55041/IJSREM37613
Volume:
8 |
9 |
Sep 2024
Pages:
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.
This paper presents the development of a nutrition chatbot that utilizes regression modeling techniques to provide personalized dietary recommendations. With the increasing prevalence of lifestyle-related health issues, there is a growing need for accessible nutrition guidance. This chatbot leverages TensorFlow for regression analysis based on user input, including dietary preferences, health goals, and nutritional needs. The model is trained on a diverse dataset to ensure accuracy in predicting optimal food choices. Our approach aims to empower users to make informed dietary decisions, enhancing their overall health and well-being.
KEYWORDS
Publication Date
9/25/2024
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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Conflict of Interest
The authors declare no conflict of interest related to this research work.
Funding Information
No funding information available for this research.
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