Principal Component, Unsupervised Learning, Dimensionality Reduction, Interview Questions, Machine Learning.
small set of connected variables into a bigger set of unrelated variables known as principal components. (B) PCA aims to keep extraneous features while retaining most of the dataset’s variability. (C) PCA is a dimensionality reduction approach that converts a big set of connected variables into a