Exploring Nutritional Data through Principal Component Analysis (PCA)

Description

This project implements Principal Component Analysis (PCA) to explore and visualize multidimensional nutritional data. Utilizing a dataset that includes various food items and their nutritional components—such as water content, energy (calories), protein, lipids, carbohydrates, and vitamins—PCA helps reduce the dimensionality of the data while preserving its variance.

This project implements Principal Component Analysis (PCA) to explore and visualize multidimensional nutritional data. Utilizing a dataset that includes various food items and their nutritional components—such as water content, energy (calories), protein, lipids, carbohydrates, and vitamins—PCA helps reduce the dimensionality of the data while preserving its variance.