## Simple And Complete Tutorial For Understanding Principal Component Analysis

Understanding Principal Component Analysis In most practical applications of data science, you will end up with data with a lot of dimensions. It is not easy to process all these dimensions because of considerations of cost and processing power limitations. These data dimensions could be highly correlated to each other so you will lose a lot of time and money, without much to show for it. Want to be a smarter data scientist and work only with uncorrelated dimensions. You have to master Principal Component Analysis. It is one of the most used techniques for dimensionality reduction. In this Post, these are the steps we are going to take to master just that:- Understand the Important Math Terms Behind PCA Singular Value Decomposition Why Principal Component Analysis Works Step By Step Implementation of PCA Tips To Be Careful About with PCA MATHS AND IMPORTANT TERMS TO KNOW BEFORE STARTING WITH[…]

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