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Today, we will discuss principal component analysis, which is not a machine learning algorithm but a technique used for reducing the dimensionality of a dataset. This involves converting multiple independent features into a new vector space with fewer dimensions. PCA can be applied to any number of features to reduce them to the desired number. This technique creates independent components based on the target dimensions. Before proceeding, please watch the complete tutorial.
