A recent but quite common observation in industry is that although there is an overall high adoption of data science, many companies struggle to get it into production. Huge teams of well-payed data scientists often present one fancy model after the other to their managers but their proof of concepts …

As Germany’s biggest online car marketplace, mobile.de provides a personalized web experience. Our Data Team leverages the interactions of our users to infer their preferences. For this tasks we often apply Python and Spark to wrangle massive amounts of data. In this talk, we are going to present …

A common pattern in most data science projects I participated in is that it’s all fun and games until someone wants to put it into production. All of a sudden the crucial question is how to deploy your model, which version, how can updates be rolled out, which requirements are needed and …

It is a widely accepted fact that we are living in the era of Big Data. Many traditional companies are looking for ways to improve their business through the virtues of Big Data and Data Science. While matured startups born in this era like Facebook and Twitter seem to naturally …

Often I get the question as a Data Scientist what the Python Data Science Stack actually is and where a beginner should start to learn. The Python ecosystem, especially around the topics such as data analytics, data mining, data science and machine learning is so vast and rich that it …