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Problem 3 (10 points): PCA
Download the "teapots. mat" data set containing 100 images of teapots of size
38 x 50. To view an image, say the second one in the data set type:
imagesc(reshape(teapotImages(2,:),38,50));
colormap gray;
Compute the data mean and top 3 eigenvectors of the data covariance matrix
and show them as images. Reconstruct the data using PCA with least squares
error using only the mean and a linear combination of the top 3 eigenvectors.
Show 10 different images before and after reconstruction. Discuss results.

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