From the course: AI Workshop: Hands-on with GANs with Deep Convolutional Networks

Course outline and prerequisites

From the course: AI Workshop: Hands-on with GANs with Deep Convolutional Networks

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Course outline and prerequisites

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Before we get to the content of this workshop, let's take a quick look at what we'll be covering today and also some of the prereqs that you need to have to make the most of your learning. Now, I make the assumption that you have some basic knowledge of how GANs work. So we'll start this workshop off by understanding how convolutional neural networks work. We'll then understand the role of convolutional layers and pooling layers in a convolutional neural network. We'll see how the discriminator is essentially just a classification model, learning to identify real and fake images. We'll understand the architecture of the constrained deep convolutional GAN, and we'll build and train a GAN using the deep convolutional network. Here are some of the prereqs that you need to get the most out of this workshop. You need to be comfortable programming in Python because we'll be writing all of our code in Python. You need to be familiar with neural networks and how they work. This is not a basic neural network course, and you should be comfortable using the PyTorch framework to build and train neural networks. I also assume that you know the fundamentals of how GANs are built and trained. And if you feel that you've never worked with GANs before, here is a course that you might want to study first, AI Workshop: Hands-on with GANs Using Dense Neural Networks. This course here is a prereq for the current workshop.

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