Explore the fundamentals of VQGAN in this first video of a three-part series, focusing on AutoEncoders with Latent Space and Reconstruction Error. Dive into the concept of AutoEncoders, understanding their structure and functionality. Examine the crucial role of Latent Space in AI and deep learning applications. Learn about Reconstruction Error and its significance in training AutoEncoders. Gain practical insights through examples and explanations, preparing you for the subsequent parts covering Variational AutoEncoders, Vector Quantized VAE, and the integration of GANs in VQGAN architecture.
All Things VQGAN - AutoEncoder with Latent Space and Reconstruction Error - Part 1
Overview
Syllabus
- Topic Introduction
- All 3 videos content
- AutoEncoder AE Intro
- AE Explanation with Example
- Latent Space
- Latent Space Deep dive
- Latent Space in AI world
- AE and Reconstruction Loss
- Reconstruction Loss Defined
- GitHub Resources
- Recap and 2nd Part Intro
Taught by
Prodramp
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