An interactive web app built with Streamlit that predicts weight change based on user input, such as age, caloric intake, activity level, sleep quality, and more. It utilizes a machine learning model to provide personalized advice and insights based on the predicted weight change.
- Predict weight change based on user input of health metrics and lifestyle factors
- Tailored insights and advice for health improvement based on prediction
- User-friendly interface with adjustable parameters for calorie intake, activity level, and stress level
- Scalable design, supporting further enhancements or additional health metrics
- Input your data: Enter your age, gender, current weight, BMR, physical activity level, and other metrics.
- View predictions: The model will output a predicted weight change along with personalized advice.
- Interpret the advice: Use the insights to make informed decisions on lifestyle changes.
- The model used is trained on a dataset with factors like caloric intake, stress level, and sleep quality.
- Weight change prediction is based on a Yeo-Johnson transformed regression model.