July 2019
Intermediate to advanced
512 pages
19h 39m
English
Content preview from Hands-On Deep Learning Algorithms with Python
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Plotting generated images
Now we plot the image generated by the generator:
n = 7 digit_size = 28figure = np.zeros((digit_size * n, digit_size * n))grid_x = norm.ppf(np.linspace(0.05, 0.95, n))grid_y = norm.ppf(np.linspace(0.05, 0.95, n))for i, yi in enumerate(grid_x): for j, xi in enumerate(grid_y): z_sample = np.array([[xi, yi]]) x_decoded = generator.predict(z_sample) digit = x_decoded[0].reshape(digit_size, digit_size) figure[i * digit_size: (i + 1) * digit_size, j * digit_size: (j + 1) * digit_size] = digitplt.figure(figsize=(4, 4), dpi=100)plt.imshow(figure, cmap='Greys_r')plt.show()
The following is the plot of the image generated by a generator:
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O’Reilly covers everything we've got, with content to help us build a world-class technology community, upgrade the capabilities and competencies of our teams, and improve overall team performance as well as their engagement.Julian F.
I wanted to learn C and C++, but it didn't click for me until I picked up an O'Reilly book. When I went on the O’Reilly platform, I was astonished to find all the books there, plus live events and sandboxes so you could play around with the technology.Addison B.
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I'm always learning. So when I got on to O'Reilly, I was like a kid in a candy store. There are playlists. There are answers. There's on-demand training. It's worth its weight in gold, in terms of what it allows me to do.