Skip to content

Exploring machine unlearning: from classification models to generative models like stable diffusion or LLMs. Inspired by 'Yesterday', it delves into removing learned data from AI models, aiming to preserve performance amid privacy and GDPR compliance challenges.

License

Notifications You must be signed in to change notification settings

mich1803/Yesterday-Machine-Unlearning

Repository files navigation

Repository banner

Yesterday (Machine Unlearning)

This project investigates the idea of machine unlearning. It begins with examples on classification models and moves on to generative models like 🖼️ picture generators or Large Language Models (LLMs). Motivated by the movie Yesterday where the lead character wakes up in a Beatles-less world, this research explores the effects and techniques of successfully 'erasing' learned data from artificial intelligence models. The goal of the project is to create methods for removing particular data from trained models in a targeted manner without compromising overall performance. This is especially important in situations where maintaining data privacy and adhering to laws like the GDPR are crucial.

About

Exploring machine unlearning: from classification models to generative models like stable diffusion or LLMs. Inspired by 'Yesterday', it delves into removing learned data from AI models, aiming to preserve performance amid privacy and GDPR compliance challenges.

Topics

Resources

License

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published