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-## **Can we predict the calories burned during a workout based on physiological statistics, workout intensity, and lifestyle habits?**
 This dataset comes from kaggle "Life Style Data", it captures detailed personal, nutritional, and fitness-related data for 20,000 individuals with 54 features. It contains health parameters such as age, weight, and BMI; exercise variables including BPM, duration, and activity type; and nutritional information such as macronutrient breakdown and meal classifications. Several derived metrics further estimate calorie balance, lean body mass, and workout effectiveness.


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8	+ ### Can we predict the calories burned during a workout based on physiological statistics, workout intensity, and lifestyle habits?
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10	This dataset comes from kaggle "Life Style Data", it captures detailed personal, nutritional, and fitness-related data for 20,000 individuals with 54 features. It contains health parameters such as age, weight, and BMI; exercise variables including BPM, duration, and activity type; and nutritional information such as macronutrient breakdown and meal classifications. Several derived metrics further estimate calorie balance, lean body mass, and workout effectiveness.
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