Sleep Quality Predictor

A Python program that predicts sleep quality as Good, Average, or Poor based on lifestyle and physiological data.

Features

• Predicts sleep quality using daily habits such as sleep duration, caffeine intake, exercise, screen time, stress, mood, and interruptions.
• Trains a supervised machine learning model on synthetic sleep data.
• Provides personalized tips to improve sleep quality.
• Includes an optional Streamlit user interface.

Files

• sleep_quality_predictor.py: Main training and prediction engine.
• app.py: Optional Streamlit interface.
• requirements.txt: Python dependencies.

Usage

1. Install dependencies:

pip install -r requirements.txt

2. Train the model or predict directly:

python sleep_quality_predictor.py

3. Run the Streamlit app:

streamlit run app.py

Notes

• The project uses synthetic data generation to simulate real-world sleep patterns.
• You can later replace the synthetic generation with a real dataset from Kaggle or UCI.
• The model uses a RandomForestClassifier and a preprocessing pipeline.