Dimensionality Reduction with PCA

Hello everyone, in this article I'll explain about PCA.
Principal component analysis (PCA) is one of the pattern recognition techniques and one of its applications is to analyse the high dimensional data that is not easy to understand by just looking at the large amount of data¹. Mathematically, PCA is a feature extraction technique that generates new feature which are linear combination of the initial feature². PCA can reduce the dimension of data to be simpler, so this technique will extract the most efficient features from the given dataset.

https://medium.com/@husfuu/pca-in-dimensionality-reduction-a667833c4c26