PCA for image compression
You'll reduce the size of 16 images with hand written digits (MNIST dataset) using PCA.
The samples are 28 by 28 pixel gray scale images that have been flattened to arrays with 784 elements each (28 x 28 = 784) and added to the 2D numpy array X_test. Each of the 784 pixels has a value between 0 and 255 and can be regarded as a feature.
A pipeline with a scaler and PCA model to select 78 components has been pre-loaded for you as pipe. This pipeline has already been fitted to the entire MNIST dataset except for the 16 samples in X_test.
Finally, a function plot_digits has been created for you that will plot 16 images in a grid.
This exercise is part of the course
Dimensionality Reduction in Python
Hands-on interactive exercise
Have a go at this exercise by completing this sample code.
# Plot the MNIST sample data
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