Code Reviews sind eine gängige Praxis in der Softwareentwicklung, doch sie sind auch in Data-Science-Projekten relevant und sinnvoll. Der Artikel beleuchtet die Gründe dafür und gibt Hinweise darauf, wie Code Reviews in Data-Science-Projekten effektiv gestaltet werden können.
In a pro-bono project facilitated by DataKind we had the great opportunity to join a team of volunteer data scientists to enable the Lwala Community Alliance to monitor the quality of their data.
At this year’s PyCon DE & PyData Berlin, we presented our learnings and experiences in two talks. These covered very different aspects of data work: On the one hand, we showcased predictive modeling applications in wind turbine maintenance and the challenges of anomaly detection. In a different presentation, we explained why code reviews are still important for data science tasks and how we can apply them to benefit from the effort.
At this year’s CorrelCon, we presented our work in the OpenDiscourse project. Leveraging techniques from natural language processing, we analyzed the speeches held in the Bundestag.