December 2017
Intermediate to advanced
536 pages
14h 23m
English
Due to its ability to reconstruct images, RBM can be used to generate more data from the existing data. We can see the original and reconstructed MNIST images by making a small helper plotting code:
row, col = 2, 8idx = np.random.randint(0, 100, row * col // 2)f, axarr = plt.subplots(row, col, sharex=True, sharey=True, figsize=(20,4))for fig, row in zip([Xtest_noisy,out], axarr): for i,ax in zip(idx,row): ax.imshow(fig[i].reshape((28, 28)), cmap='Greys_r') ax.get_xaxis().set_visible(False) ax.get_yaxis().set_visible(False)
We get the result as follows:

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