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Introduction to Diffusion Models

Gain insights into diffusion models, explore their workings and architecture, and learn to create images from noise using neural networks and pretrained models with practical implementations.

Beginner

11 Lessons

Certificate of Completion

Gain insights into diffusion models, explore their workings and architecture, and learn to create images from noise using neural networks and pretrained models with practical implementations.

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Explanations

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This course includes

5 Playgrounds

Course Overview

What You'll Learn

Course Content

Recommendations

Course Overview

In this course, you’ll gain practical insight into the theoretical concepts associated with diffusion models, complemented by hands-on expertise in creating images from noise and training neural networks for effective image sampling. You’ll start with the introduction to generative models, specifically focusing on how diffusion models fall under this category. You’ll dive deep into the intricacies of diffusion models, exploring their workings, architecture, and the theoretical foundations supporting them. ...Show More

In this course, you’ll gain practical insight into the theoretical concepts associated with diffusion models, complemented by ha...Show More

TAKEAWAY SKILLS

Artificial Intelligence

Transformer Models

Modeling and Simulation

Image Manipulation

What You'll Learn

An understanding of the fundamental concepts and principles underlying diffusion models

Working knowledge of theoretical concepts associated with diffusion models

Hands-on experience in leveraging state-of-the-art diffusion models available to perform various tasks using the Diffusers library

Working knowledge of how diffusion models work, their needs, and benefits

Hands-on experience in image generation, neural network training, and sampling

An understanding of the fundamental concepts and principles underlying diffusion models

Course Content

Course Overview

1 Lessons

Get familiar with diffusion models, their applications, and foundational skills in data science.

Introduction to the Course

Getting Started

5 Lessons

Look at the fundamentals, tasks, challenges, and applications of diffusion models.

Generative Models

What Are Diffusion Models?

Diffusion Model Tasks

Challenge: Depth-to-Image Generation

The Need, Benefits, and Applications of Diffusion Models

Image Creation from Scratch

3 Lessons

Work your way through U-Net setup, model training, and sampling for image creation.

Setting up the Neural Network

Model Training

Sample Creation

Wrapping Up

1 Lessons

Grasp the fundamentals of generative diffusion models, image transformations, and practical applications.

Conclusion

Appendix

1 Lessons

Take a look at installing the Diffusers library for working with advanced diffusion models.

Installing Diffusers Library

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