July 2019
Intermediate to advanced
512 pages
19h 39m
English
Content preview from Hands-On Deep Learning Algorithms with Python
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Starting the GAN!
First, we feed the noise 
to the generator and it will output the fake image, 
:
fake_x = generator(z)
Now we feed the real image to discriminator 
and get the probability of the real image being real:
D_logits_real = discriminator(x)
Similarly, we feed the fake image to discriminator and get the probability of the fake image being ...
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