# Snippet from the repository (Simplified) def make_generator(): model = Sequential() model.add(Dense(4*4*1024, input_shape=(100,))) model.add(Reshape((4,4,1024))) model.add(Conv2DTranspose(512, (5,5), strides=(2,2), padding='same')) model.add(BatchNormalization()) model.add(LeakyReLU(alpha=0.2)) # ... more layers to upscale to 64x64x3 return model
: Links and scripts to download the data used in the book's examples. Where to Access the Content Official Code Repository : GANs-in-Action on GitHub gans in action pdf github
Before diving into the code, let's address why this specific book has become a staple in the data science community. gans in action pdf github