Food_Calorie_Estimator.py

[expanse88]

The Food Calorie Estimator is a machine learning tool designed to predict the number of calories in various food items based on their macronutrient content—specifically the amount of carbohydrates, proteins, and fats they contain. This estimator uses a dataset that maps different food items to their nutritional values, and it employs a Random Forest Regressor model to make accurate predictions of calorie counts.

Key Features:
Inputs: Macronutrient data (carbohydrates, proteins, fats) for different food items.
Model: A Random Forest Regressor, which is a powerful and flexible ensemble learning algorithm that improves prediction accuracy by building multiple decision trees.
Scaling: The input data is standardized to ensure consistency and better performance in predictions.
Output: Predicted calorie content for any given food item based on its macronutrient composition.

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