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Data Science Collective

With the beginning of the 2019 summer semester students of the courses of Computational Sciences and Media Informatics formed a student group to jointly explore Big Data and help each other with the design and execution of individual research projects.

Who we are

Knowledge creates² Data is a project at Universität Regensburg. It combines research efforts in Big Data, Artificial Intelligence and machine learning across all faculties.

Machine learning in enterprises

A growing number of companies in the Regensburg area optimize and enhance their productivity by using Artificial Intelligence – in conjunction with the universities of Regensburg.

Kick-off workshop: Innovation network “AI for mobility”

The E-Mobility Cluster Regensburg and the Ostbayerische Technische Hochschule Regensburg will initiate a research and development network (R&D) to develop new technologies for mobility based on artificial intelligence. The network is part of the Regensburg AI initiative Applied Artificial Intelligence in Regensburg AIR. The virtual kick-off workshop that will take place on 2020-09-30, is adressed […]

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Info-Webinar “Artificial Intelligence – Perspectives from Practice”

A few years ago, Artificial Intelligence (AI) was more of a promise than a reality. Today, AI systems are used for a wide variety of applications and functions and more and more companies are seeing AI as a key technology. After initial successes in the laboratory, it is often difficult to use these AI applications […]

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Info webinar “Artificial Intelligence”

The domain of ​​”Artificial Intelligence” has made rapid progress in recent years. The potential for medium-sized companies is great – but so are the challenges to remain internationally competitive. With this webinar, artificial intelligence becomes tangible. The basic approaches will be presented and applied independently by you as a participant. Finally, you can use practical […]

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Workshop: Artificial intelligence in health

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 and development as well as in medical care. This particularly includes machine learning in imaging diagnostics. Here, AI supports the attending physician, for example in […]

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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 strategy. It is about future joy and the readiness to innovate, e-government and related services for citizens, the digital competence of city administrations and civil […]

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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 tech company that has grown from 3 to over 150 employees within a few years and which has a research-driven philosophy as one of its […]

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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 University of Bozen-Bolzano. In her very positive report, she speaks, among other things, about offered courses, the recognition of course achievements, accommodation, formalities and financing. […]

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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 bias, are discussed in the introduction to active learning. Then an effective way of circumventing it by balancing exploring and exploiting accordingly is given via […]

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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” data science perspective? Well, it’s certainly not just one … This is again a double bill but with a twist as you will be drawn […]

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