Skip to content

In How Diffusion Models Work, you will gain a deep familiarity with the diffusion process and the models which carry it out. More than simply pulling in a pre-built model or using an API, this course will teach you to build a diffusion model from scratch.

Notifications You must be signed in to change notification settings

Ryota-Kawamura/How-Diffusion-Models-Work

Repository files navigation

In How Diffusion Models Work, you will gain a deep familiarity with the diffusion process and the models which carry it out. More than simply pulling in a pre-built model or using an API, this course will teach you to build a diffusion model from scratch.

In this course you will:

  • Explore the cutting-edge world of diffusion-based generative AI and create your own diffusion model from scratch.
  • Gain deep familiarity with the diffusion process and the models driving it, going beyond pre-built models and APIs.
  • Acquire practical coding skills by working through labs on sampling, training diffusion models, building neural networks for noise prediction, and adding context for personalized image generation.
  • At the end of the course, you will have a model that can serve as a starting point for your own exploration of diffusion models for your applications.

This one-hour course, taught by Sharon Zhou will expand your generative AI capabilities to include building, training, and optimizing diffusion models.

Hands-on examples make the concepts easy to understand and build upon. Built-in Jupyter notebooks allow you to seamlessly experiment with the code and labs presented in the course.

About

In How Diffusion Models Work, you will gain a deep familiarity with the diffusion process and the models which carry it out. More than simply pulling in a pre-built model or using an API, this course will teach you to build a diffusion model from scratch.

Topics

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published