Deep Convolutional Generative Adversarial Networks (DCGAN)

Learn to create Generative Adversarial Networks (GAN) & Deep Convolutional Generative Adversarial Networks (DCGAN)

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What You Will Learn!

Learn the basic principles of Generative Adversarial Networks (GAN)
Learn the basic principles of Deep Convolutional Generative Adversarial Networks (DCGAN)
Build a Deep Convolutional Generative Adversarial Networks (DCGAN) with step by step guidance
Setup the code for Deep Convolutional Generative Adversarial Networks (DCGAN)

Description

Generative Adversarial Networks (GANs) & Deep Convolutional Generative Adversarial Networks (DCGAN) are one of the most interesting and trending ideas in computer science today.

Two models are trained simultaneously by an adversarial process. A generator , learns to create images that look real, while a discriminator learns to tell real images apart from fakes.

At the end of the Course you will understand the basics of Python Programming and the basics ofGenerative Adversarial Networks (GANs) & Deep Convolutional Generative Adversarial Networks (DCGAN) .

The course will have step by step guidance

Import TensorFlow and other libraries

Load and prepare the dataset

Create the models (Generator & Discriminator)

Define the loss and optimizers (Generator loss , Discriminator loss)

Define the training loop

Train the model

Analyze the output

Suggested Prerequisites:

Python coding: some revision is provided during this course
Gradient descent
Basic knowledge of neural networks

Who Should Attend!

Anyone who wish to improve the deep learning knowledge
students who wish to learn the new trends Deep Convolutional Generative Adversarial Networks (DCGAN)

TAKE THIS COURSE