ADAPT : Awesome Domain Adaptation Python Toolbox
Antoine de Mathelin, Mounir Atiq, Guillaume Richard, Alejandro de la, Concha, Mouad Yachouti, Fran\c{c}ois Deheeger, Mathilde Mougeot, Nicolas, Vayatis
TL;DR
The paper presents ADAPT, an open-source Python library that simplifies access to various transfer learning and domain adaptation methods, integrating with popular ML frameworks and offering extensive documentation and examples.
Contribution
It introduces a user-friendly, open-source Python toolbox for domain adaptation compatible with scikit-learn and TensorFlow, with comprehensive documentation and examples.
Findings
Facilitates easier access to domain adaptation techniques
Supports integration with scikit-learn and TensorFlow
Provides extensive online documentation and examples
Abstract
In this paper, we introduce the ADAPT library, an open source Python API providing the implementation of the main transfer learning and domain adaptation methods. The library is designed with a user friendly approach to facilitate the access to domain adaptation for a wide public. ADAPT is compatible with scikit-learn and TensorFlow and a full documentation is proposed online https://adapt-python.github.io/adapt/ with a substantial gallery of examples.
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Taxonomy
TopicsDomain Adaptation and Few-Shot Learning · Topic Modeling · Multimodal Machine Learning Applications