This paper presents the implementation and Analysis of two different techniques of dimensionality reduction for a given dataset. One being linear(PCA) and other being non-linear(Autoencoder). The analysis involves the implementation of an autoencoder and PCA for reconstructing the dataset using the MINST dataset and the Wine dataset.
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PCA vs Autoencoder
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