[Diffusion Models]Neural Network Architecture
In How Diffusion Models Work, you will gain insight into the diffusion process and the models that enable it. Rather than using pre-built models or APIs, this course teaches you how to build diffusion models from scratch.
In this course you will:
Explore the frontier world of diffusion-based generative AI and create your own diffusion models from scratch. Gain insight into the models driving the diffusion process, going beyond pre-built models and APIs. Gain practical coding skills by completing labs on sampling, training diffusion models, building neural networks for noise prediction, and adding context for personalized image generation. By the end of the course, you will have a model that can be used as a starting point for explorations of diffusion models in your own applications. This one-hour course, taught by Sharon Chow, will expand your generative AI capabilities, including building, training, and optimizing diffusion models.
Hands-on examples make concepts easy to understand and build upon. The built-in Jupyter Notebook allows you to seamlessly experiment with the code and labs presented in the course.
For more content, please pay attention to:[Diffusion Models]How Diffusion Models Work