PyData Berlin Meetup, hosted by eBay Tech Berlin, talks by Dr. Florian Wilhelm, and Ulrike Thalheim

Causal Inference and Propensity Score Methods (by Dr. Florian Wilhelm)

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.

Dr. Florian Wilhelm is a data scientist at inovex GmbH, an IT project house with a focus on digital transformation. His focus lies on mathematical modelling, predictive & prescriptive analytics as well as machine learning including deep learning. He enjoys working with the Python ecosystem and data science stack to which he also contributed several extensions. Dr. Florian Wilhelm studied mathematics and earned his PhD with his work on "Parallel Preconditioners for an Ocean Model in Climate Simulations" at the Karlsruhe Institute of Technology.

Open Data Use Cases (by Ulrike Thalheim)
In her talk, Ulrike Thalheim of the OK Lab Berlin gives a quick overview of the open data use cases that the German open data community currently deals with. The presented projects measure air quality with a sensor on balconies (http://luftdaten.info/), try to make election data more accessible (https://codefor.de/wahlsalons/), build up a massive database of structured knowledge (https://www.wikidata.org) and campaign for opening up transport data in order to improve routing services (https://rettedeinennahverkehr.de/).

Ulrike Thalheim has been an active member of Berlin's Open Data community since 2014 when she joined the OK Lab (http://codefor.berlin). She also serves as one of its 5 co-lab leads. The OK Lab Berlin is one of more than 20 Open Knowledge Labs around Germany that are all combined together as Code for Germany. Ulrike's main interests are digital solutions around migration, election data and fostering a welcoming community.
This meetup was organized by PyData Berlin and hosted by the eBay Tech teams in Berlin. We are software developers, testers, data engineers & scientists as well as site operations teams from eBay Germany, eBay Kleinanzeigen, mobile.de and MOTOR-TALK.
We build leading online platforms using the latest technologies and methods.

Meet us in person at our next Tech Talk in Berlin: https://www.meetup.com/eBay-Europe-Technology .

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