Barely a week passes without the announcement of yet another (seed) funding round for a startup, which claims to utilize “artificial intelligence”, “deep learning”, “machine learning” or “proprietary algorithms”. Algorithms, it seems, are at the core of almost all ventures these days – is that really the case?

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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Übersättigung im Profifußball: Wie viele Zuschauer kommen zu Fußballspielen?

Bei vielen Freundschaftsspielen der deutschen Fußballnationalmannschaft – wie jüngst gegen England – sind in letzter Zeit einige Sitzplätze frei geblieben. DFB-Teammanager Oliver Bierhoff warnte bereits vor einer “Übersättigung” des Fußballs. Gibt es generalisierbare Treiber für die Beliebtheit einer Fußball-Partie? Ein kleines Experiment – abseits der großen Fußballbühne.

A Question of Data Quality

80% of work in data science projects is dedicated to data quality assessment, data preparation and integration. Applying and tweaking the algorithms, improving the performance of models (basically all the fun stuff) covers only 20%. What’s the reason for this?

3,2,1 – Gone! The Science of Used Car Pricing

Despite the recent Volkswagen scandal, German cars still have a world-class reputation. And Germans still love cars: more than 44 million vehicles are registered, that’s about one car for every second citizen. Understandably, the used car market is also large – but, how does one arrive at a fair value for a used car?

Cambridge Analytica: Beyond the Hype

The story immediately went viral: Big Data company Cambridge Analytica and its sophisticated psychographic models helped Donald Trump to secure the victory in the 2016 presidential election. The story played to all prevalent fears in the age of big data: privacy, microtargeting, behavioural steering. But now – with far less media buzz – the company admits that it was never really involved in the Trump campaign. What can we learn from this ‘scam’?

Data Science & Online Dating

It’s one of the most notable features of e-commerce websites like Amazon: the recommendation engine. “Based on your purchasing history you might also enjoy the following books”. Data Science has been fuelling the advancement of these recommendation engines, increasing conversions to order. But while matching people to products is one thing, matching people to people is a different kind of endeavour – how successfully is data science informing online dating?

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.