This time 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 founding principles. This talk […]
Read MoreData Science @ Regensburg: Life in a Research-driven Tech Scaleup…
Another special edition of Data Science @ Regensburg. Over the last few months all sorts of data science issues were explored but one aspect has only been touched in passing, and so we thought it’s time to rectify this and focus on logging and log data. For this purpose we have invited two excellent speakers […]
Read MoreData Science @ Regensburg: Logging & Log Data Special…
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. Then an effective way of circumventing it by balancing exploring and exploiting accordingly is given via Thompson sampling. Lastly active learning is […]
Read MoreIntroduction to active learning for classification…
A special edition of Data Science Meetup that is dedicated to look at COVID-19 from a data science perspective. The evening will start with Jimmy Lin who will join us to answer YOUR questions. For many years he has been a key figure in a variety of areas ranging from search to natural language processing. […]
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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Using Games-With-A-Purpose to Label NLP Data: Lessons from the Last Ten Years
Read MoreMassimo Poesio…