Generative AI Models: Generating Data Using Variational Autoencoders

Generative AI    |    Intermediate
  • 8 videos | 1h 17m 39s
  • Includes Assessment
  • Earns a Badge
Rating 5.0 of 2 users Rating 5.0 of 2 users (2)
Variational autoencoders (VAEs) represent a powerful variant of traditional autoencoders, designed to address the challenge of generating new and diverse samples from the learned latent space. VAEs introduce probabilistic components, incorporating a probabilistic encoder that maps input data to a distribution in the latent space and a decoder that reconstructs data from samples drawn from this distribution. Begin this course by discovering how variational autoencoders can be used for generating images. Next, you will create and train VAEs in Python and the Google Colab environment. Then you will construct the encoder and decoder. Finally, you will train the VAE on multichannel color images. Upon course completion, you will have a solid understanding of variational autoencoders and their use in generating images.

WHAT YOU WILL LEARN

  • Discover the key concepts covered in this course
    Provide an overview of variational autoencoders (vaes)
    Describe the architecture of vaes
    Create a vae
  • Train a vae
    Train a convolutional vae
    Train a vae on color images
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 1m 43s
    In this video, we will discover the key concepts covered in this course. FREE ACCESS
  • 12m 15s
    After completing this video, you will be able to provide an overview of variational autoencoders (VAEs). FREE ACCESS
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    3.  Variational Autoencoder Implementation
    11m 2s
    Upon completion of this video, you will be able to describe the architecture of VAEs. FREE ACCESS
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    4.  Setting up the Variational Autoencoder
    12m 18s
    In this video, find out how to create a VAE. FREE ACCESS
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    5.  Training a Variational Autoencoder
    13m 31s
    During this video, you will learn how to train a VAE. FREE ACCESS
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    6.  Training a VAE Using Convolutional Networks
    12m 33s
    Discover how to train a convolutional VAE. FREE ACCESS
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    7.  Training VAEs on Multichannel Images
    11m 37s
    In this video, you will learn how to train a VAE on color images. FREE ACCESS
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    8.  Course Summary
    2m 41s
    In this video, we will summarize the key concepts covered in this course. FREE ACCESS

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