ADS Meetup: A-Z of Data Science

Ever wondered how Data Science can be applied to every-day problems? In A-Z of Data Science we heard from three Data Scientists about the work they’ve carried out, from identifying the problem to how they used Data Science to solve it.

On Thursday 24th October, ADS hosted A-Z of Data Science at the University of Amsterdam, 904 Science Park. This Meetup was specifically geared to providing insight into how Data Science is used in real life use-cases. The Chair for the evening was Marieke van Erp, Lead Digital Humanities Lab at KNAW.

To start off the Meetup, Daan Odijk, Lead Data Scientist at RTL showcased the many challenges that face a broadcaster. This includes delivering online content more personally and making the lives of content editors easier when preparing television content.

Daan described various projects he is working on to optimize the user experience for the RTL online broadcasting platform. This includes text analytics for their search results to computer vision and labeling emotions during television series. RTL uses a diverse set of skills and techniques to improve the service they offer.

Chantal von Son, PhD candidate in Computational Linguistics at Vrije Universiteit Amsterdam, talked about her current research in the Computational Lexicology and Terminology Lab (CLTL). Her work focuses on finding contradicting information in and across texts. For instance when one fact is in conflict with another, or when two people express different perspectives towards the same statement.

In the age of ‘alternative facts’, ‘fake news’ and ‘filter bubbles’, Chantal hopes to contribute to more complete, transparent and balanced access to information for web users.  In this talk her use case was the online vaccination debate, which has been one of the most heated and polarised debate topics for years now, and the impact of which on public health is evident.

The final talk came from Flavia Barsotti and Gilles Verbokhaven from ING. ING was happy to see that their joint presentation by the teams of Risk & Pricing Advanced Analytics and Model Risk worked for the audience and as well as for the presenters Flavia and Gilles.

For a bank like ING, increasingly data and models are key assets that should be managed as such. There’s a strong driver to accelerate, since global banks like ING have to deal with regulatory changes every 12 minutes! ING is open to collaborate with the science community, regarding open source initiatives like ‘Probatus’ and next generation ‘responsible’ and ‘explainable’ products and services, e.g. for online ‘instant’ lending.

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