Welcome to the repository of the ITS.ML research project. For more information on the project itself, please visit our homepage, have a look at our concept slides here or get in touch with us on Twitter @_its_ml.
This repository contains the code of all notebooks presented on our homepage, exemplifying how machine learning approaches may be used to address challenges for industrial practice. Additionally, we provide here datasets for benchmarking ML approaches that were generated in the course of this project.
As each notebook requires specific dependencies, we suggest to set up a virtual python environment for running individual notebooks. Instructions on how to do so either using virtualenv (installation guide) or conda (installation guide) can be found within the README.md of the respective notebook.
Note that all notebooks were tested on python 3.7.