DEEP training facility
Distributed training facility for Machine Learning, Artificial Intelligence and Deep Learning models.
Institute of Physics of Cantabria (IFCA)
- Provided by:
PSNC, Karlsruhe Institute of Technology, Institute of Informatics - Slovak Academy of Sciences , National Distributed Computing Infrastructure, Institute of Instrumentation for Molecular Imaging - Grid and High Performance Computing - Universitat Politècnica de València, Italian National Institute of Nuclear Physics
- Scientific domain:
Distributed training facility for Machine Learning, Artificial Intelligence and Deep Learning models. This service offers a set of tools to build and train Machine Learning, Artificial Intelligence and Deep Learning models in distributed e-Infrastructures. Ready to use models are available for transfer learning or reuse. The DEEP-Hybrid-DataCloud is providing machine learning and deep learning scientists with a set of tools that allow them to eﬀectively exploit the existing compute and storage resources available through EU e-Infrastructures for the whole machine learning cycle. The DEEP training facility provides tools for building training, testing and evaluating Machine Learning, Artificial Intelligence and Deep Learning models over distributed e-Infrastructures leveraging GPU resources. Models can be built from scratch or form existing and pre-trained models (transfer learning or model reuse). Features: - Transparent training over distributed e-Infrastructures with GPU access. - Docker based for model portability and reusability. - Easy model integration with standards-based REST APIs. - CLI and web user interface to interact with the system. - OpenID Connect based identity.
- Image/Data Analysis
- Machine Learning
- Artificial Intelligence
- Developer Tools
Resource availability and languages