This dataset is a synthetically generated health & lifestyle dataset containing 100,000 records of individuals with various lifestyle and health indicators. It is designed to support machine learning, data science, and statistical modeling tasks such as: Classification (e.g., predict disease risk based on lifestyle factors) Regression (e.g., estimate cholesterol levels from daily habits) Clustering (e.g., group people by lifestyle similarities) Feature engineering & EDA practice The dataset does not contain real personal information; all values are artificially generated while maintaining realistic distributions.