Answer / Vaibhav Tyagi

Principal Component Analysis (PCA) is a popular technique that transforms the data into a new coordinate system, retaining most of the variance in fewer dimensions. Another method is t-distributed Stochastic Neighbor Embedding (t-SNE), which attempts to preserve local and global structure of high dimensional data while reducing its complexity. Other techniques include Independent Component Analysis (ICA) and Local Linear Embedding (LLE).

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