All Things VQGAN - AutoEncoder with Latent Space and Reconstruction Error - Part 1
Offered By: Prodramp via YouTube
Course Description
Overview
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.
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
Related Courses
Introduction to Artificial IntelligenceStanford University via Udacity Natural Language Processing
Columbia University via Coursera Probabilistic Graphical Models 1: Representation
Stanford University via Coursera Computer Vision: The Fundamentals
University of California, Berkeley via Coursera Learning from Data (Introductory Machine Learning course)
California Institute of Technology via Independent