Digitalveranstaltungen in Bonn und Region

+++ Corona-Info +++ Wir gehen aktuell davon aus, dass keine der Präsenzveranstaltungen stattfindet. Der Digitalkalender besitzt bis auf Weiteres also keine Gültigkeit. Wenn sich die Wogen geglättet und der Kalender wieder aktualisiert ist, entfernen wir diese Botschaft.
Events, die mit ✅ gekennzeichnet sind, sind überprüft und finden auf jeden Fall online statt.

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Hacking HR Rhine-Ruhr @ Deutsche Telekom HQ
Jul 17 um 18:00 – 21:30

We BELIEVE that HR can be the most important pioneer and trailblazer to propel organizations and their people forward into the future of work.

Our purpose in Hacking HR is simple: create the best HR that has ever existed. We are focused at the intersection of future of work, technology and HR.

How do we want to do that? By creating a global community of HR people interested in the future of work and the intersection of tech and HR, and providing the most valuable tools so that the community is 100% ready for the future of work. There’s never been a better time for HR in the history of business. It is our time!

Automated Machine Learning – Hype or Next Big Thing? @ Digital Hub Bonn
Okt 7 um 19:00 – 21:00

Hallo, es ist uns endlich wieder gelungen einen erstklassigen Sprecher für unser Meetup zu gewinnen: Mathias Kirsten, Senior Data Scientist im Bereich Technology & Innovation der Deutschen Telekom AG, wird uns im November zu folgendem Thema aufschlauen (in Englisch):

Automated Machine Learning has become a hot topic in the past two years. Players like DataRobot, H2O or SparkBeyond are pushing the topic onto the Data Science agenda and Company Managers are buying into the marketing message of “Democratizing AI”: Conjuring up expectations to substitute missing Data Scientists by giving data savvy business experts access to such tools. The latter one being a claim that we have heard of again and again with every new generation of Visual Data Analytics platforms since their first appearance in the late 1990s.
Time for a reality check!
In this session, I am going to show and discuss results we obtained at Deutsche Telekom by employing one of the currently most sophisticated Auto Machine Learning tools available on-premise. Benchmarking the tool on several application domains against human Data Scientists as well as other Auto ML tools, I am going to put our findings into perspective with the Data Mining life cycle and show where Auto ML tools actually provide substantial support – but also where it falls short of the expectations and high hopes. Finally, I will conclude with an outlook on the role of Data Scientists and the future relevance of Automated Machine Learning.