At Axel Springer, Europe’s largest digital publishing house, we own a lot of news articles from various media outlets such as Welt, Bild, Business Insider and many more. Arguably, the most important part of a news article is its title, and it is not surprising that journalists tend to spend a fair amount of their time to come up with a good one. For this reason, it was an interesting research question for us at Axel Springer AI whether we could create an NLP model that generates quality headlines from Welt news articles (see Figure 1). This could, for example, serve our journalists as inspiration for creating SEO titles, which our journalists often don’t have time for (in fact we’re working together with our colleagues from SPRING and AWS on creating a SEO title generator).

Open source machine learning and data visualization for novice and expert. Interactive data analysis workflows with a large toolbox.

CleverCSV provides a drop-in replacement for the Python csv package with improved dialect detection for messy CSV files. It also provides a handy command line tool that can standardize a messy file or generate Python code to import it.

You may have heard about Bandersnatch, an interactive film released on Netflix as part of the Black Mirror series. I’ve heard about it when it was released, but didn’t get around to watch it until recently, and I was surprised at how deep and thorough the implementation is.

Analysis and numbers of the Bandersnatch interactive film.

The missing link between spreadsheets and data visualization.

Tracking happiness is very simple. This section explains the method used for tracking happiness

A iPython notebook that introduces how to use the topicmodels module for implementing Latent Dirichlet Allocation using the collapsed Gibbs sampling algorithm of Griffiths and Steyvers (2004). The module contains three classes: one for processing raw text, another for implementing LDA, and another for querying. This tutorial will go through the main features of each, for full details see the documented source code.