Introduction to Diffusion Models

In this diffusion models course, you will 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

In this diffusion models course, you will 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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Explanations

This course includes

6 Playgrounds

This course includes

6 Playgrounds

This course has a GPU-powered coding session. Do I have access to it?

GPU-enabled code execution will let you query state of the art models on custom prompts
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Course Overview

In this course, you’ll gain practical insight into the theoretical concepts associated with diffusion models and hands-on expertise in creating images from noise and training neural networks for effective image sampling. You’ll start with an introduction to generative models, focusing on what is a diffusion model, specifically focusing on how diffusion models fall under this category. You’ll dive deep into how diffusion models work, exploring their workings, architecture, and the theoretical foundations su...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

What You'll Learn

An understanding of the fundamental concepts and principles underlying diffusion models

Course Content

Course Overview

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

Introduction to the Course

Getting Started

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

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

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

Conclusion

Appendix

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

Installing Diffusers Library

Data Augmentation for ML Datasets

Project

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