SleepLifeInsights is a machine learning initiative that analyzes lifestyle factors and sleep patterns to forecast the quality of sleep. The initiative uses a dataset that includes a variety of health metrics and sleep-related parameters to offer a comprehensive understanding of sleep health.
- Prediction based on lifestyle factors
- Examination of the relationship between sleep quality and physical activity
- Assessment of the influence of stress levels on sleep patterns
- Interactive visualizations of sleep health metrics
The Sleep Health and Lifestyle Dataset is employed in the project, and it comprises the subsequent essential features: Dataset Link : https://www.kaggle.com/datasets/uom190346a/sleep-health-and-lifestyle-dataset
- Person ID
- Gender
- Age
- Sleep Duration
- Quality of Sleep
- Physical Activity Level
- Stress Level
- Heart Rate
- Daily Steps
- Occupation
- BMI Category
- Blood Pressure
- Sleep Disorder
- python
- pandas
- numpy
- scikit-learn
- matplotlib
- seaborn
- jupyter
- Clone the repository git clone https://github.com/yourusername/SleepQualityPredictor.git
cd SleepQualityPredictor
- Create and activate a virtual environment (optional but recommended)
python -m venv venv
- Install required packages
pip install -r requirements.txt
sleep_health_analysis/
│
├── data/
│ └── Sleep_health_and_lifestyle_dataset.csv
│ ├── notebooks/
│ └── sleep_quality_performance.ipynb
│ ├── tests/
│ └── test_sleep_quality.py
│ ├── requirements.txt
├── README.md
└── LICENSE
Ceren Kaya Akgün - @cerenekeye