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DEEP testbed

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DEEP Preview-Testbed exposing enhanced DEEP-Rosetta services is now available for users to experience the ease of building, developing, training and deploying machine learning models and exploiting

Integrating HPC resources with PaaS Cloud approach in DEEP-HybridDataCloud project

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Typically the HPC environments are characterized by software and hardware stacks optimized for maximum performance at the cost of flexibility in terms of OS, system software and hardware

Collaboration partnership between DEEP-Hybrid-DataCloud and EOSC DIH

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We are pleasured to announce that DEEP-Hybrid-DataCloud consortium has signed a collaboration agreement with EOSC-DIH, aiming at boosting the dissemination of DEEP offering and fostering the

Event-Driven Execution of DEEP Open Catalog Modules for Prediction on Amazon Web Services

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The DEEP Open Catalog provides ready to use modules for Artificial Intelligence, Machine Learning and Deep Learning models that can be executed in a wide variety of computing platforms. These

Training your model with the DEEP platform is now easier than ever.

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The second DEEP release was recently published and it comes with plenty of new useful functionalities, all of them with the common goal of easing the path for the scientific communities to develop,

DEEP-Hybrid-DataCloud announces the availability of the second software release and platform

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New platform release allows data scientists and machine learning practitioners to build, develop, train and deploy machine learning services easily, with a comprehensive set of tools and

DEEP Marketplace

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We are glad to present an open ecosystem to foster the exchange of machine learning modules in the scientific community: the DEEP Marketplace. The catalogue includes all the applications developed

Our Newsletter #1 is out!

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The first Deep-HybridDataCloud Newsletter is out! Take a look to the first issue of the newsletter here! It includes: An overview of the project including a summary of the main objectives

Hybrid Virtual Elastic Clusters Across Clouds

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Virtual clusters provide the required computing abstraction to perform both HPC (High Performance Computing) and HTC (High Throughput Computing) with the help of a LRMS (Local Resource Management

DEEP Webinar

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Worried about the learning curve to introduce Deep Learning in your organization? Don’t be. The DEEP-HybridDataCloud project offers a framework for all users, including non-experts, enabling the

This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 777435.

Unless otherwise indicated, all materials created by the DEEP-Hybrid-DataCloud consortium are licensed under a Creative Commons Attribution 4.0 International License.

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