Projects Last Projects
Domain Adaptation
Lior Grauer and Eden Konopnicki
Supervised by Tal Neoran, Roy Velich
Abstract
In our project we implemented a domain adaptation model, Domain adaptation refers to the process of adapting a machine learning model trained on a source domain to perform effectively on a target domain. The ultimate goal of domain adaptation is to enable models to generalize well across different domains, allowing them to perform accurately and reliably in real-world settings.
Pictures
Project Report
Please, see project report.
Final Presentation
Please, see final presentation.