Introduction
Overview of generative adversarial networks (GANs)
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1. Understanding Convolutional and Pooling Layers
Course outline and prerequisites
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Setting up Google Colab cloud-hosted notebooks
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Understanding convolutional neural networks
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Transforming multichannel image to tensor
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Applying convolutional and pooling layers
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Viewing the effect of different filters
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2. Training a Discriminator as a Classification Model
Types of convolutional layers
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Training data for discriminator bad fakes and real images
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Loading and transforming training image data
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Understanding the discriminator architecture
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Training a discriminator on bad fakes
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Training data for discriminator good fakes and real images
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Training a discriminator on good fakes
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3. Training a Deep Convolutional GAN
Generator and discriminator
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Deep convolutional GANs (DCGANs)
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Setting up data for GAN training
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Setting up the generator and discriminator
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Examining the ouput from an untrained generator and discriminator
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Setting up the GAN training loop
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Viewing GAN training results
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Conclusion
Summary and next steps
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Ex_Files_GANs_Deep_Convolution.zip
(416.0 MB)