Deep Convolutional Generative Adversarial Networks (DCGAN)

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

Requirements Basic neural networks knowledge would be helpful, however all the basic concepts will be covered in this course