Machine learning for predictive maintenance: where to start?

Think about all the machines you use during a year, all of them, from a toaster every morning to an airplane every summer holiday. Now imagine that, from now on, one of them would fail every day. What impact would that have…

Integrating Pandas and scikit-learn with pipelines

Integrating Pandas and scikit-learn with Pipelines

Scikit-learn and Pandas are both great tools for explorative data science. Both require a bit of practice to get the hang of. The…

Forecasting beer sales for HEINEKEN’s customers

As one of the world’s leading brewers, HEINEKEN works together with its customers to offer a diverse array of over 250 brands to consumers in over 170 countries, of which 70 have breweries present. One of the leading challenges in serving…

Genetic Algorithms in Practice

A Genetic Algorithm (GA) is part of a family of algorithms known as Evolutionary Computing. These algorithms are all inspired by biological evolution, used for various optimizations. In this post we discuss what type of projects used Genetic Algorithms and provide a…

Why do Big Data projects fail and how to make it succeed?

Big Data has the goal to automate delivery of actionable business insights from data. In order to do this, you often end up wanting diverse data sources, large data sets and a vast amount of computational power. However, most are…

How to obtain advanced probabilistic predictions for your data science use case

Many data science use cases involve predicting a continuous quantity. For instance, a grid operator might want to predict the energy consumption level for a group of households for next week…

Key takeaways from the Scala days keynote

RE-WORK Deep Learning Summit London

On the 21th and 22nd of September we attended the RE-WORK Deep Learning Summit in London. This event was focused on the development of deep learning techniques and business applications based on deep learning. Facebook and Amazon presented their Natural Language…

Peeking into the Big Data future: Lessons learned from the DataWorks Summit in Munich

For about a year I have been fully submerged in everything regarding Big Data; working with various tools and techniques throwing a bit of data science in the mix. I realized there is…