<ul><li>PCA is a technique used to highlight variation and bring out strong patterns in a dataset.</li><li>The main objective of PCA is to identify the directions (principal components) where the data varies the most and project the data onto these new axes to simplify it.</li><li>By reducing the number of dimensions, PCA helps in focusing on the most important information without getting lost in the noise.</li><li>PCA is a powerful tool for breaking down complex data and improving data analysis and insights.</li></ul>

Understanding Principal Component Analysis

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