Too Long; Didn't Read
Pramod Chandrayan is a Product Engineering Consultant at FarmArt @FarmArt | AIML | Data Science. He is the author of a book called Principal Components Analysis. He uses the Principal Component Analysis (PCA) to reduce the dimensionality (i.e., from 20 to 2/3), so it is much easier to visualize the shape and the data distribution. In order to deal with this high dimensionality problem, we came up with the concept of PCA, where we filter out mathematically which features are important.