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Build a Stable Diffusion VAE From Scratch using Pytorch

Build a Stable Diffusion VAE From Scratch using Pytorch

Free

Master the foundational skills to create a Variational Autoencoder (VAE) for Stable Diffusion from scratch using PyTorch. This course covers the entire development pipeline, from theory to implementation, enabling you to build robust VAEs for advanced image generation tasks.

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Has discount
Expiry period Lifetime
Made in English
Last updated at Mon Dec 2024
Level
Intermediate
Total lectures 1
Total quizzes 0
Total duration 01:00:00 Hours
Total enrolment 0
Number of reviews 0
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Short description Master the foundational skills to create a Variational Autoencoder (VAE) for Stable Diffusion from scratch using PyTorch. This course covers the entire development pipeline, from theory to implementation, enabling you to build robust VAEs for advanced image generation tasks.
Outcomes
  • Understand the theory and mathematics of Variational Autoencoders (VAEs).
  • Build and train a complete VAE using PyTorch.
  • Optimize VAEs for integration into Stable Diffusion models.
  • Evaluate and deploy VAEs for real-world image generation tasks.
  • Gain the confidence to experiment with advanced generative AI models.
Requirements
  • Intermediate Python programming skills
  • Understanding of neural networks and deep learning concepts
  • Familiarity with linear algebra and probability

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