Machine Learning, Data Science, Deep Learning, Dimensionality Reduction, Artificial Intelligence.
it works: Standardization: First, PCA scales your data to have a mean of 0 and a standard deviation of 1. This step ensures that no variable dominates the others just because of its scale. Covariance Matrix: PCA calculates how each variable is related to the others, which is known as the covariance