Introduction to Generative Adversarial Networks (GAN) with Apache MXNet


Introduction to Generative Adversarial Networks (GAN) with Apache MXNet


GANs are a type of deep neural network that allow us to generate data. In this webinar, we’ll take a look at the concept and theory behind GANs, which can be used to train neural nets with data that is generated by the network. We’ll explore the GAN framework along with its components -- generator and discriminator networks. We’ll then learn how to use Apache MXNet on AWS using the popular MNIST dataset, which contains images of handwritten numbers. In the end, we’ll create a GAN model that is able to generate similar images of handwritten numbers from our test dataset.

When: September 26 | 10:30 AM - 11:10 AM PT | 01:30 PM - 02:10 PM ET

Learning Objectives:
• Learn about the benefits of using the Apache MXNet framework for deep learning
• Learn about Generative Adversarial Networks for data generation
• Learn how to use Apache MXNet on AWS with the MNIST dataset

Who Should Attend: AI developers, non-AI developers, data scientists, IT practitioners

Speakers: Sunil Mallya, AWS Deep Learning Solutions Architect, AWS & Yash Pant, Associate Solutions Architect, AWS

Register for the Webinar