Explanation
Introduction to Diffusion Models This course delves into the fascinating world of diffusion models, from the initial research paper to the development of narrower applications such as image generation, painting, animations, and more. Combining a theoretical approach, and hands-on implementation using PyTorch, this course will equip you with the knowledge and experience needed to excel in this exciting field of Generative AI. From Theory to Practice: The course begins by dissecting the initial research paper on diffusion models, explaining the concepts and techniques from scratch. Once you have a deep understanding of the underlying principles, we will generate the results of the initial expansion model paper, from scratch, using PyTorch.
Advanced Image Generation: Based on basic knowledge, we will delve into advanced image generation techniques using diffusion models. Painting and DALL-E-like Applications: Discover how diffusion models can be used in painting, enabling you to fill in missing or damaged parts of images with incredible precision. After this session, you will have a deeper understanding of how diffusion works with models such as Stable Diffusion or DALL-E, and you will have the knowledge needed to modify it for your needs. Dive into Stable Extensions: Gain a deeper understanding of Stable Extensions and their inner workings by reviewing and analyzing the source code. This will enable you to effectively leverage the stability of your industrial and research projects, beyond using the API.
What will you learn?
- How the Diffusion Model Works
- Implementing Diffusion Models from Scratch Using PyTorch
- A deeper understanding of painting Diffusion models
- Deep analysis of stable diffusion: opening the black box
- Creating high quality animations with Diffusion Models
- Reviewing influential research papers
Who is this course for?
- For engineers and programmers
- For students and researchers
- For entrepreneurs, CEOs and CTOs
- Passionate about machine learning
An Introduction to Diffusion Patterns
- Publisher: Udemy
- Teacher: Maxime Vandegar
- Language: English
- Level: Medium
- Number of courses: 48
- Duration: 8 hours and 3 minutes
The course covers 2023/10
Requirements
- Basic programming knowledge
- Basic Machine Learning knowledge
Pictures
Sample Clip
Installation Guide
Extract files and watch your favorite player
Subtitle: Not available
Quality: 720p
Download Links
Password file: free download software
file size
3.13 GB