Generating Images In recent studies, Groundbreaking research has been done using diffusion models to generate images. However, previously other models were used to perform that task. Image Generation has multiple application in Industries (NFT Creation, Virtual Tryouts, Deep Fake Generation..)
AutoEncoders is a project created to explore the power of autoencoders in various machine learning and deep learning applications. Autoencoders are neural networks used for tasks such as data compression, denoising, and feature extraction. This project provides a collection of practical examples and use cases that demonstrate how autoencoders can be utilized in real-world scenarios.
- Clone the AutoEncoders repository to your local machine:
git clone https://github.com/rayaneghilene/AutoEncoders.git
We welcome contributions to AutoEncoders. If you would like to contribute or report issues, please follow these guidelines:
- Use the GitHub issue tracker to report bugs or request features.
- Fork the repository and make your changes on a feature branch.
- Create a pull request with a clear description of the changes you made.
This project is licensed under the MIT License - see the LICENSE.md file for details.
If you have any questions or would like to discuss my work further, please don't hesitate to contact me at [email protected].
This repository was created by GHILENE Rayane. The labs were adapted from the course materials provided by Tharsan Senthivel at ENSEA.