Yesterday and today I attended the data2day, a conference about Big Data, Machine Learning and Data Science in Heidelberg, Germany. Topics and workshops covered a range of topics surrounding (big) data analysis and Machine Learning, like Deep Learning, Reinforcement Learning, TensorFlow applications, etc. Distributed systems and scalability were a major part of a lot of the talks as well, reflecting the growing desire to build bigger and more complex models that can’t (or would take too long to) run on a single computer.

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I have written the following post about Data Science for Fraud Detection at my company codecentric’s blog: Fraud can be defined as “the crime of getting money by deceiving people” (Cambridge Dictionary); it is as old as humanity: whenever two parties exchange goods or conduct business there is the potential for one party scamming the other. With an ever increasing use of the internet for shopping, banking, filing insurance claims, etc.

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