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Deep Learning for Digital Content Creation with Autoencoders

This workshop teaches deep learning techniques to design, train, and deploy neural networks for digital content creation through a series of hands-on exercises. You will work with widely-used deep learning tools, frameworks, and workflows by performing neural network training on a fully-configured, GPU-accelerated workstation in the cloud. The workshop teaches techniques for transferring the look and feel of an image, as well as autoencoder- based techniques to enhance image quality.

You’ll also learn methods to detect noise and train your own denoiser on some sample images. By the end of the workshop, you will be able to create paintings from your photographs, make noise-free images from noisy ones, and convert low-resolution images to high-resolution images.

Course Prerequisites

  • Basic familiarity with deep learning concepts, such as convolutional neural networks (CNNs)
  • Experience programming in Python

Deep Learning for Digital Content Creation with Autoencoders Key Facts
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