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D6.1 – State-of-the-art DEEP Learning (DL), Neural Network (NN) and Machine Learning (ML) frameworks and libraries

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This document provides an overview of the state-of-the-art in Deep Learning (DL), Neural Network (NN) and Machine Learning (ML) frameworks and libraries to be used as building blocks in the DEEP Open

New publication: “Machine Learning and Deep Learning frameworks and libraries for large-scale data mining: a survey”

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We are thrilled to announce that we have published a new paper entitled "Machine Learning and Deep Learning frameworks and libraries for large-scale data mining: a survey" on the Springer Artificial

D4.2 – First implementation of software platform for accessing accelerators and HPC

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This deliverable describes the first implementation of the software platform for accessing accelerators and HPC. The list of components included in the software platform is based on the analysis

D5.2 – High Level Hybrid Cloud solutions prototype

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This document complements deliverable D5.1 Definition of the Architecture of the Hybrid Cloud (D5.1) with the specific prototype developments carried out to support the deployment of

D6.3 – First prototype of the DEEP as a Service

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This document provides an updated description of the prototype implementation of the DEEP as a Service solution that is being developed within the DEEP-Hybrid-DataCloud project Work Package 6 (WP6).

D3.2 – Pilot testbed and integration architecgture with EOSC large scale infrastructures

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The deliverable contains the plan, design, architecture and deployment of the Pilot Preview testbed based on technical requirements and descriptions from the WP2 use cases. The services

DEEP-Genesis: first software release is out

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The first DEEP-HybridDataCloud software release is out! The DEEP-HybridDataCloud project is pleased to announce the availability of its first public software release, codenamed DEEP Genesis.

DEEP Hybrid DataCloud accepted paper in 22nd International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES2018), Sep 3-5, 2018, Belgrade, Serbia

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We are proud to announce that a research paper developed under the Deep Hybrid DataCloud Project has been accepted for inclusion in 22nd International Conference on Knowledge-Based and Intelligent

Digital Infrastructures for Research 2018 (DI4R) and IBERGRID 2018

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The third edition of the annual Digital Infrastructures for Research (DI4R) conference was hold this year at the University Institute of Lisbon (ISCT-IUL), from October 9th to 11th. Co-located with

Report on the workshop: New challenges in Data Science: Big Data and Deep Learning on Data Clouds in Santander (Spain)

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The Spanish National Research Council (CSIC) as coordinator of the DEEP-Hybrid-DataCloud project has organized together with the eXtreme-DataCloud project the “New challenges in Data Science”

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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