A complete end-to-end project analyzing a synthetic sleep and lifestyle dataset. The project includes data cleaning, exploratory data analysis (visualizations), feature engineering, and machine learning modeling to predict sleep disorders. Built using Python, Pandas, Seaborn, Matplotlib, and Scikit-learn.

Survey Flask app, created in purpose to collect sleep assessment data, preprocess them and draw conclusions - available on the project website.