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Deep Learning: Introduction to GANs

Generative Adversarial Networks with Python and Tensorflow


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Description

In this course you will learn from scratch how to implement GANs to any of your projects. We will start with by breaking down a GAN into its parts and analyzing them. Then we will look at the loss functions we will be using and the Frechet Inception Distance. Finally we will take all this new information and apply it using Python and Tensorflow to the MNIST dataset. The code will be written such that you can use it for any of your image-based projects.

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