AI-Powered Personalized Fitness and Diet Recommendation System Using Machine Learning and Deep Learning Techniques

Registration ID: IJNRD_324406

Published ID: IJNRD2605098

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Himanshu Tyagi, Honey Pal, Ashu Kaushik, Dishant Sharma

Artificial Intelligence, Machine Learning, Deep Learning, Personalized Recommendation System, Fitness Tracking, Diet Planning, Collaborative Filtering, Convolutional Neural Network, Reinforcement Learning, Digital Health

The Increasing number in the cases of lifestyle related health problems nowadays like Obesity, Diabetes, Blood Pressure, and also Heart Disease indicates the urgency of personalized health managment system. Existing system tends that they are genric but they failed to manage the specific characteristic of an individual like physiological metrics, physical activities, eating habits, and health objective like blood pressure, Obesity etc. .In this Regards this study contributes an Ai-Powered Personalized Fitness and Diet recommendation system using Machine Learning (ML) and Deep Learning (DL) techniques to make personalized diet recommendation system, This purposed system consist of f convolutional Neural Network (CNN) to mark the physical activities of user, collabrative filtering is done on the basis of recommendation algorithm for nutritional recommenda- tions, and reinforcement learning (RL) for making feedback. The physical stat of user like body weight, age etc. and health related information like Exercise, Diet etc are processed by multi model pipeline in order to make the relevant recommendation at any required time

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Himanshu Tyagi, Honey Pal, Ashu Kaushik, & Dishant Sharma (May-2026). AI-Powered Personalized Fitness and Diet Recommendation System Using Machine Learning and Deep Learning Techniques. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 11(5), a890-a894. https://ijnrd.org/papers/IJNRD2605098.pdf

Volume 11 Issue 5, May-2026

Pages : a890-a894

Paper Reg. ID: IJNRD_324406

Published Paper Id: IJNRD2605098

Research Area: Other area not in list

Author Type: Indian Author

Country: Ghaziabad, Uttar Pardesh, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2605098.pdf

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