Event description:

1st talk/Global Flood Event Monitoring (Lukas Csoka – Data Scientist, Swiss Re)

One of the common perils that causes huge damage loses is flood. It is important to known for insurance companies, which areas are affected by floods. Traditional flood models yield only a limited amount of information at the time of the event. Identifying affected areas after a flood is currently an almost completely manual process. Combining traditional flood models, social media and a number of other information sources, we want to create a detailed and accurate picture of the damage as it happens.

2nd talk/Machine learning in customer behavioral analytics (Martin Kupec – Data Scientist, Swiss Re)

Having a portfolio of customers paying for service on regular basis is very frequent case, not just in insurance, but also in telecommunications, entertainment and many other retail industries. The speaker will have a talk about how to get insights for such a portfolio, about lapses or migrations towards different services within portfolio. Dynamic pricing for targeted customer segments is valuable, but is hard to get using traditional approach. However, in the presented use case, we tried non-traditional approach with machine learning classification models leading us to very interesting and reasonable results.

Event is sponsored by Swiss Re (budget for drinks and refreshment).

LinkedIn: https://www.linkedin.com/in/lukas-csoka/ & https://www.linkedin.com/in/kupecmartin/

@Meetup.com group's event here (https://www.meetup.com/PyData-Bratislava/events/249702852/) & @Eventbrite registration here (https://www.eventbrite.com/e/pydata-bratislava-meetup-9-swiss-re-edition-tickets-45098900024) (if you use both your seat is guarateed). +our event you can find also @Facebook here (https://www.facebook.com/events/216807835744945/).

[Disclaimer: If you just mark "going" @Facebook event we can't guarantee your seat]

Language of the event: R, Slovak & English

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PyData Bratislava [Python Data Enthusiasts and Users, Data Scientists & Statisticians of all levels from Slovakia]
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This meetup group is for Data Scientists, Statisticians, Economists and Data Enthusiasts using Python for data analysis and data visualization. The goals are to provide Python enthusiasts a place to share ideas and learn from each other about how best to apply the language and tools to ever-evolving challenges in the vast realm of data management, processing, analytics, and visualization.
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PyData is a group for users and developers of data analysis tools to share ideas and learn from each other. We gather to discuss how best to apply Python tools, as well as those using R and Julia, to meet the evolving challenges in data management, processing, analytics, and visualization. PyData groups, events, and conferences aim to provide a venue for users acrossall the various domains of data analysis to share their experiences and their techniques. PyData is organized by NumFOCUS.org, a 501(c)3 non-profit in the United States.

The PyData ​Code of Conduct​ governs this meetup. To discuss any issues or concerns relating to the code of conduct or the behavior of anyone at a PyData meetup, please contact the organizer or NumFOCUS Executive Director Leah Silen (+1512-222-5449; leah@numfocus.org).
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Our Facebook group you can find here: https://www.facebook.com/groups/1813599648877946/

Our Twitter account here: https://twitter.com/PyDataBA

Our LinkedIn group here: https://www.linkedin.com/groups/13506080

All materials from previous meetups on GitHub here: https://github.com/GapData/PyData
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Organizers:
GapData Institute (https://www.gapdata.org/) (GDI) is a nonprofit nonpartisan research institution harnessing power of data & wisdom of economics for public good.

|| Data. Think. Change. ||
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NumFOCUS (http://www.numfocus.org/) is a 501(c)(3) nonprofit that supports and promotes world-class, innovative, open source scientific computing. The mission of NumFOCUS is to promote sustainable high-level programming languages, open code development, and reproducible scientific research. We accomplish this mission through our educational programs and events as well as through fiscal sponsorship of open source data science projects. We aim to increase collaboration and communication within the scientific computing community.