Answer Posted / Kavita

Methods of reducing dimensionality in machine learning include Principal Component Analysis (PCA), Linear Discriminant Analysis (LDA), t-SNE, and autoencoders. These techniques aim to find lower-dimensional representations of the original data while preserving essential information.

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