Overview / Usage

In this project, we aim to create an intelligent system that can recommend personalized diets for individuals based on specific parameters like age, type of diet(vegan/non-vegan), weight, and height. The system will use machine learning algorithms to analyze these parameters to generate results if they are healthy or not and the diet they have to maintain.

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Methodology / Approach

In this project, we have used two popular machine learning algorithms, KMeans, and Random Forest, to build a diet recommendation system. KMeans algorithm has been used to cluster individuals based on their dietary preferences, while Random Forest has been used to predict the most suitable diet plan for each cluster.
The system takes input from the user regarding their age, gender, weight, height, physical activity level, and dietary restrictions. Based on this information, the system uses KMeans to cluster the user into a specific group based on their dietary preferences. Then, the Random Forest algorithm is used to suggest a personalized diet plan for each cluster, taking into account the individual's nutritional requirements and dietary restrictions.
Overall, this diet recommendation system provides a practical and data-driven approach to help individuals make informed decisions about their diets. By leveraging the power of machine learning algorithms, we can provide personalized recommendations that are tailored to each individual's unique needs and preferences.

Repository

https://github.com/balakrishna1202/Hackathon

Collaborators