How predictable is voter behavior? Could big data really swing an election? The past US presidential campaign and the debate about the effectiveness of Cambridge Analytica have fueled the discourse about the role of data in election campaigning.

About our Blog

This blog is a place for us to reflect on data science, AI, and machine learning. Hence, it covers a broad array of topics: technical considerations, our view on certain industries, interviews with researchers, thought leaders, and industry experts, as well as light-weight visualisation.

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A visit at the Do Good Data conference

Corporations are becoming more and more aware of how the growing availability of data will impact and transform their business model. But also in the nonprofit world, data literacy and analytical capacity is a key factor.

(Errors in) Communicating Statistics: Base rate neglect

When the results were in on last June 26th, most of those watching were surprised or even shocked that a majority of Britons had just voted to leave the EU. Even among those who cast their vote for “Leave”, many said they had not anticipated the vote to come out in their favour, and some even stated they had “not wanted it to happen”.

PEAT – Deep Learning und Pflanzenkrankheiten

Data Science ist in der Landwirtschaft angekommen und ein junges Start-up aus Hannover sorgt in der Szene aktuell für Furore: PEAT nutzt Deep Learning zur Erkennung von Pflanzenkrankheiten. Robert Strey, CTO und Co-Founder, erklärt im Interview die Technologie und Vision des Unternehmens.

Data Science & Real Estate

While online real estate platforms like immoscout24 in Germany employ large cohorts of data scientists, traditional real estate brokerage firms have been rather conservative in adopting more data driven approaches. But there is dynamism: We talked to Nathaniel Holland, Chief Research and Data Scientist of Houston-based NAI Partners, about how he is introducing data science into the sector.

Navigating the Biomedical Data Landscape – Part II

Data science is revolutionizing pharmaceutical R&D; and knowing how to navigate the open data landscape is key to the revolution.

Navigating the Biomedical Data Landscape – Part I

Data science projects are successful when they produce actionable results over several years. Since databases constitute the foundation of those endeavours, their selection is highly strategic, and the biomedical field is no exception to that rule.

idalab talks: Towards Scalable Fraud Detection – a journey from Sklearn to Spark

The new season of idalab talks, will begin on January 20th with Stanimir Dragiev and Tammo Krueger, who will discuss “Towards scalable fraud detection: a journey from Sklearn to Spark”. The talk will start at 4:00 pm.

#HACKMCFC, Data Science & Football

After a long, potentially over-stretched UEFA European Championship this summer, football took a well deserved break in July. While gossip around Pogba and Ibrahimovic kept supporters of Manchester United busy, followers of Manchester City took on a different endeavor: #HACKMCFC was the first-ever event, which brought together data scientists and digital enthusiasts from across Europe to answer one question: How can data science help to transform the game?

“We need to develop tools which empower domain experts to find insights”: Interview with Patrick Lucey

In a multi-billion business such as sports, data science can provide teams the crucial edge to success in a highly competitive environment. We talked to Patrick Lucey, Director of Data Science at STATS about the challenges and opportunities of data science in professional sports.