Question: why pca is used in machine learning?
Answer: Principal Component Analysis (PCA) is an unsupervised, non-parametric statistical technique primarily used for dimensionality reduction in machine learning. ... Models also become more efficient as the reduced feature set boosts learning rates and diminishes computation costs by removing redundant features.