End-to-end Machine Learning project about Predictive Maintenance. Given a data-set of industrial data, the first step is data analysis and preprocessing. The next step is searching for efficient models with good performances on training and, mostly, testing data. A special focus lies on finding models as comprehensible as possible for humans.
The task of this problem is to classify machine failures so that, with given industrial feature values, engineers can be supported in decision making.