Is your company interested in hosting meetups? Get in touch so we can help.

PyData Berlin April Meetup

April 19, 19:00

Berlin, Germany
Office Club, Prenzlauer Berg, Pappelallee 78/79, 10437, Berlin

External Registration

Open Registration Page

Grand Welcome to our April meetup hosted by Mobile.de at Office Club Prenzlauerberg.

Doors open at 19:15 and we have two speakers,
Dr. Ulricke Thalheim, Lab lead at OK Lab Berlin (www.codefor.berlin)
Talk: Open Data Use Cases

Abstract: The talk will give a quick overview about the open data use cases that the German open data community currently deals with. I will talk about how different projects generate data, scrape data, demand data from agencies, and finally edit and use data. The presented projects measure air quality with a sensor on balconies, try to make election data more accessible, build up a massive database of structured knowledge (Wikidata) and campaign for opening up transport data in order to improve routing services. Most of the projects are developed in the spare time. The talk aims to show some of the enthusiasm and diversity we encounter when working on digital propositions and solutions for today’s society.

Dr. Florian Wilhelm, Innovex GmbH
Talk: Causal Inference and Propensity Score Methods
Abstract: In the field of machine learning and particularly in supervised learning, correlation is key in order to predict the target variable with the help of feature variables. Rarely do we think about causation and the actual effect of a single feature variable or covariate on the target or response respectively. Some even go so far saying that “correlation trumps causation” like in the book “Big Data: A Revolution That Will Transform How We Live, Work, and Think” by Viktor Mayer-Schönberger and Kenneth Cukier. Following their reasoning with Big Data there is no need anymore to think about causation since nonparametric models will do just fine using only correlation. For many practical use-cases this point of view seems to be acceptable but surely not for all. In my talk I will present the theory of causal inference and demonstrate it's application with the help of inverse probability of treatment weighting (IPTW) which is a propensity score method on a practical use-case.

Looking forward to seeing you there! And, as always, please remember to update your RSVP to ensure others have a chance to join.

PyData Berlin PyData Berlin

Propose talk to PyData Berlin