Conditional GAN in TensorFlow | Generative Adversarial Networks | Deep Learning
In this video, we're going to use the TensorFlow framework to make our very own Conditional GAN.
A Conditional Generative Adversarial Network (Conditional GAN) is a type of machine learning model that goes beyond standard GANs by allowing users to influence and guide the generation of realistic data based on specific conditions or labels.
Code:
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Timeline:
00:00 - Introduction
00:39 - Dataset
01:09 - Importing Libraries and Functions
01:28 - Image Dimensions
01:44 - Defining Some Helper Functions.
04:38 - Generator Neural Network
07:48 - Discriminator Neural Network
09:31 - Training Function for GAN
14:09 - Function to Save Generated Images
14:35 - Training the GAN
25:35 - Testing the GAN (Generating Fake Images)
30:03 - Conclusion
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