Artificial intelligence (AI) is becoming one of the most important initiators of digital innovation – in general and in the health sector too. AI is already being used in research […]
Smart City Regensburg?
New ideas for politics, administration and civil society in digitization At the end of the last term of office the city council of Regensburg decided on a Smart City framework […]
Data Science @ Regensburg: Life in a Research-driven Tech Scaleup
This time @ Data Science Regensburg we welcome Signal AI’s Principal Data Scientist Dyaa Albakour. Dyaa will give us some insight into what it is like to work in a […]
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ERASMUS experience report
Isabel Red, master student of Information Science at the University of Regensburg, has shared her experience report on her Erasmus stay. From 2019-09-15 to 2020-02-29 she was at the Free […]
Data Science @ Regensburg: Logging & Log Data Special
Another special edition of Data Science @ Regensburg about Logging & Log Data Special. Over the last few months all sorts of data science issues were explored but one aspect […]
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Introduction to active learning for classification
Active learning is, in essence, about maximizing the performance gain (of an underlying, supervised machine learning algorithm) per label. Some possible (query) strategies and the core problem emerging, being sampling […]
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Data Science Meetup
We are very pleased to announce a special edition of our Data Science Meetup that is dedicated to looking at COVID-19 from a data science perspective. Did I say “a” […]
Charlie Hull
The right path to making search relevant
Charlie’s talk describes three aspects of search quality, focusing on relevance, and describes how to measure and improve it and tools for doing so.
Thursday, 2019-10-31, 18:00, H26 (VG).
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Massimo Poesio
Using Games-With-A-Purpose to Label NLP Data: Lessons from the Last Ten Years
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