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.