Deic Interactive HPC
Once again The University Libraries at The Royal Danish Library invite students and staff from the Danish Universities to join us in a datasprint to grabble with digital methods like data wrangling and text and data mining.
The topic is democracy and political negotiations in t…
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A new set of Danish deep learning models for natural language processing (NLP) was trained in UCloud. Danish NLP has in recent years obtained considerable improvements with the addition of multiple new datasets and models. However, at present, there is no coherent framework for applying state-of-the-art models for Danish. We present DaCy: a unified framework for Danish NLP built on SpaCy. DaCy uses efficient multitask models which obtain state-of-the-art performance on named entity recognition, part-of-speech tagging, and dependency parsing.
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Learn how to apply AI tools, techniques and algorithms to real-life problems.
You will study the core concepts of Deep Neural Networks, how to build Deep Learning models as well as how to measure and improve the accuracy of your models. You will also learn essential data pre-processing techniques to ensure a robust Machine Learning pipeline.
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Are you developing software or tools that are driven by research/engineering in either academia or industry? Need to network, share knowledge and experiences with your peers?
Nordic-RSE invites everyone interested to join and shape the agenda of our lightweight get-together. The program will consist mainly of your contributions and we encourage you to submit a short abstract for a discussion topic, talk, demonstration, or any other type of program you would like to run beforehand…
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One Danish research group can get the unique opportunity to make their metadata machine actionable in a 2 x 1/2 day event – free of charge. The concept is developed by researchers for researchers.
The aim of the M4M WS is to work practically on how to improve your metadata and make them machine-actionable, thus complying with the Findable, Accessible, Interoperable and Reusable (FAIR) principles.
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During the first wave of Covid-19 information decoupling could be observed in the flow of news media content. The corollary of the content alignment within and between news sources experienced by readers (i.e., all news transformed into Corona-news), was that the novelty of news content went down as media focused monotonically on the pandemic event. This all-important Covid-19 news theme turned out to be quite persistent…
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