At this year’s PyCon DE & PyData Berlin, we presented our learnings and experiences in two talks: Polars, an alternative data-wrangling library to the well-known Pandas library and in a second talk insights we gained from building an internal QA-Chat system, even before ChatGPT and it’s buzz started.
Rückblick zur Konferenz DataLift Summit und Informationen zum dort gehaltenen Workshop zu visueller Datenexploration mit Python
Zur Verstärkung unserer Teams in Karlsruhe, Köln und Hamburg suchen wir Data Scientists / Data Engineers.
Die erfolgreiche Umsetzung von Daten-Projekten erfodert einen gekonnten Umgang mit den elementaren Werkzeugen. Für das Heise Machine Learning Sonderheft haben wir eine Einführung in PyData Tools wie NumPy, Pandas und Scikit-Learn geschrieben.
AutoML is the process of automatically applying machine learning to real world problems, which includes the data preparation steps such as missing value imputation, feature encoding and feature generation, model selection and hyper parameter tuning. Even though the research field on AutoML exists at least since its first dedicated workshop at ICML in 2014, real world usage just got applicable recently. This blog post compares the AutoML offerings of AWS, Google and Microsoft in a qualitative fashion.