Update README.md

README.md

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 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.
 
-The numeric target variable will be calories_burned. 
+The numeric target variable will be **calories_burned**. 
 
 **The predictor variables:**
 
-Physiological: age, Gender, Weight (kg), Height (m), Fat_percentage, BMI, Resting_BPM
+> Physiological: age, Gender, Weight (kg), Height (m), Fat_percentage, BMI, Resting_BPM
 
-Workout: Session_duration (hours), Avg_BPM, Max_BPM, Workout_Type, Experience_Level, Workout_Frequency (day/week)
+> Workout: Session_duration (hours), Avg_BPM, Max_BPM, Workout_Type, Experience_Level, Workout_Frequency (day/week)
 
-Lifestyle: Water_Intake (liters), diet_type
+> Lifestyle: Water_Intake (liters), diet_type
 
 **Project overview**