Data Science Meetup Hamburg

This is a past event

156 people went

Location image of event venue


!!! New Location @ !!!

=== Doors open @ 6:30 ===

=== Networking ===

=== Small intro ===

=== Break & Networking ===

=== Talk 1 ===

RLgraph: Robust, incrementally testable reinforcement learning by Kai
Fricke, Postdoc @ Helmut-Schmidt-Universität Hamburg.

In this talk, we will introduce RLgraph, a modular reinforcement
learning library. Utilizing a strict separation of concerns, RLgraph
makes it easy to build, test and debug reinforcement learning
algorithms, or to just use well-tested off-the-shelf algorithms for
optimization problems. This talk will introduce the library, discuss the
challenges we faced implementing the library, and touch the topic on how
you can extend the library to fit your needs.

=== Talk 2 ===

Fabian Braun Algorithm Egineer at MOIA on features beat algorithms - Improving Card Fraud Detection through Suspicious Pattern Discovery

In this talk we will introduce the topic of credit card fraud from a
data science perspective.

Then we show how frequent pattern mining can be used to improve card
fraud detection. According to our hypothesis fraudsters use stolen
credit card data at specific, recurring sets of shops. We exploit this
behavior to identify fraudulent transactions. In a first step we show
how suspicious patterns can be identified from known compromised cards.

Then we define new attributes which capture the suspiciousness of a
transaction indicated by known suspicious patterns. Eventually a
non-linear classifier is used to assess the predictive power gained
through those new features. The new attributes lead to a significant
performance improvement compared to state-of-the-art aggregated
transaction features. Our results are verified on real transaction data
provided by our industrial partner.

=== Networking ===

=== Closing ===