Machine learning and statistics with python

Introduction to PCA analysis                          project and writing: shyambhu mukherjee, solanki kundu Introduction: PCA(principal component analysis) is one of the major mathematical techniques used regularly behind dimension reduction, feature reduction, and low dimensional visualizations. PCA is dependent on the idea of eigenvalue decomposition of symmetric matrices .  Summary of article: In this article, we will start with basic concept of PCA and discuss the various ways to perform PCA visualizations and results. Then, once you are down with basics and usage, we will get into the linear algebra behind PCA; discuss why and how eigenvalues come into picture and how to practically use PCA, choose dimensions and all that. By the end of this article, you will be confident to use and explain PCA analysis. If you already use pca, still I guess this article w...