This course introduces diffusion models, a family of machine learning models that recently showed promise in the image generation space. Diffusion models draw inspiration from physics, specifically thermodynamics. Within the last few years, diffusion models became popular in both research and industry. Diffusion models underpin many state-of-the-art image generation models and tools on Google Cloud. This course introduces you to the theory behind diffusion models and how to train and deploy them on Vertex AI.
Introduction to Image Generation with Google Cloud
Free Course
Learn what diffusion models are, how they work, and real use-cases for them.
Estimated time
Approx. 1 Hour
Skill level
Intermediate
Prerequisites
See prerequisites in detail
In collaboration with
About this course
What you will learn
Introduction to Image Generation with Google Cloud
- How diffusion models work.
- Real use-cases for diffusion models.
- Unconditioned diffusion models.
- Advancements in diffusion models (text-to-image).
Prerequisites and requirements
General experience in machine learning, deep learning, convolutional neural networks (CNNs), and Python programming.
See the Technology Requirements for using Udacity.
Why take this course?
This course will familiarize you with diffusion models, a promising family of machine learning models widely used in image generation. Diffusion models serve as the foundation for numerous cutting-edge image generation models and tools available on Google Cloud. Throughout the course, you will gain a comprehensive understanding of diffusion model theory, along with practical knowledge on training and deploying these models on Vertex AI.
Learn with the best.
Google Cloud Training
Built in collaboration with Google Cloud Training