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This repo is for the Linkedin Learning course: Hands-On Generative AI with Diffusion Models: Building Real-World Applications

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Hands-On Generative AI with Diffusion Models: Building Real-World Applications

This is the repository for the LinkedIn Learning course Hands-On Generative AI with Diffusion Models: Building Real-World Applications. The full course is available from LinkedIn Learning.

Hands-On Generative AI with Diffusion Models: Building Real-World Applications

As AI and machine learning applications become increasingly powerful and pervasive, it’s essential that developers know how to apply generative models, regardless of their industry or current role. Given the projected future demand for AI professionals, this hands-on, skills-based course is designed to equip you with the tools and technical know-how required to get you up to speed building real-world applications and stay apace with current and emerging trends.

Learn how to leverage some of the most recent advancements in generative AI with diffusion models by exploring the power of the Hugging Face diffusers library. Join instructor and generative AI expert Nayan Saxena as he dives into unconditional image generation, text-guided image generation, image-to-image translation, the art of image inpainting, image quality and efficiency improvements, music generation, and more. By the end of this course, you'll be adept at applying these models in real-world scenarios.

Instructions

This repository has branches for each of the videos in the course. You can use the branch pop up menu in github to switch to a specific branch and take a look at the course at that stage, or you can add /tree/BRANCH_NAME to the URL to go to the branch you want to access.

Branches

The branches are structured to correspond to the videos in the course. The naming convention is CHAPTER#_MOVIE#. As an example, the branch named 02_03 corresponds to the second chapter and the third video in that chapter. Some branches will have a beginning and an end state. These are marked with the letters b for "beginning" and e for "end". The b branch contains the code as it is at the beginning of the movie. The e branch contains the code as it is at the end of the movie. The main branch holds the final state of the code when in the course.

When switching from one exercise files branch to the next after making changes to the files, you may get a message like this:

error: Your local changes to the following files would be overwritten by checkout:        [files]
Please commit your changes or stash them before you switch branches.
Aborting

To resolve this issue:

Add changes to git using this command: git add .
Commit changes using this command: git commit -m "some message"

Instructor

Nayan Saxena

Deep Learning Expert

Check out my other courses on LinkedIn Learning.

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This repo is for the Linkedin Learning course: Hands-On Generative AI with Diffusion Models: Building Real-World Applications

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