In machine learning, PCA stands for Principal Component Analysis. PCA is used to tackle a known ML problem when a dataset has a large number of features, i.e. high dimensions, also known as the curse of dimensionality. The ML feature engineering engineering techniques available are classified into feature selection and feature extraction techniques. Dimensionality reduction ... Read more