Author: aloga

Home » Articles Posted by aloga

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

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 services covering the whole machine learning application lifecycle. The new DEEP as a Service allows to deploy machine learning models as services, following a serverless approach, with horizontal […]

Paving the path towards the implementation of the EOSC ecosystem

The European Open Science Cloud (EOSC) aims to be the Europe’s virtual environment for all researchers to store, manage, analyse and re-use data for research, innovation and educational purposes. INDIGO-DataCloud (INDIGO) and its two follow-up projects, Deep-HybridDataCloud (DEEP) and eXtreme-DataCloud (XDC) are considered to be part of the key contributors to the actual implementation of […]

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

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 Intelligence Review Journal. The paper, that is published as Open Access and can be downloaded following its doi: 10.1007/s10462-018-09679-z, is authored by Giang Nguyen, Stefan Dlugolinsky, […]

DEEP-Genesis: first software release is out

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

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.

Licencia de Creative Commons