Diabetes prediction

The dataset comprises 600 daily records from 20 individuals, each entry representing health and activity metrics relevant to diabetes prediction. It includes 10 features such as step count, heart rate, sleep hours, calories burned, workout minutes, stress level, weight, and a binary target variable Diabetic (0 = non-diabetic, 1 = diabetic).

All values are complete with no missing data, making it ideal for machine learning applications. The dataset supports binary classification tasks, enabling the development of predictive models to assess diabetes risk based on daily lifestyle patterns.