Machine Learning Based Yoga Recommendation System for the Physical Fitness

• Published in: 2023 Eighth International Conference on Science Technology Engineering and Mathematics (ICONSTEM) pp. 1 - 7
• Main Authors: Baruah, Anganabha, Madhavi Koti, Valli, Pandey, Vivekanand, Gungewale, Savita Mohan, Reddy, N Srikanth, Gupta, Monika
• Format: Conference Proceeding
• Language: English
• Published: IEEE 06.04.2023
• Subjects: Machine learning; Mathematical models; Physical fitness; Psychology; Pulmonary diseases; Solids; Support vector machines; Vegetation; Yoga recommendation system
• DOI: 10.1109/ICONSTEM56934.2023.10142367

A recommendation system's goal is to expect client interests and derive their points of view. This system can furnish clients with the data they require in light of their necessities and keeping in mind that thinking about their inclinations. To improve recommendations, the information should be all the more completely dissected. At the point when individuals take in critical chilly, their safe systems can be hindered. At the point when there is no physical movement during the day, flu occasionally influences invulnerability and respiratory lot infection. Physical movement fortifies an individual's insusceptible system. The people who overchill are more inclined to infections since it requires more work to keep them at an ordinary internal heat level. This study made a system for anticipating physical fitness utilizing information on calorie consumption, race, orientation, inclinations, and medical issue. The proposed recommendation system makes practice recommendations in light of the client's inclinations while considering comorbidities, geographic areas, and exercise and eating ways of behaving.