Very basic examples showing how you can use OpenSTEF in a jupyter notebook on your local machine.

You can also use Binder to explore the notebooks in an online, interactive environment.

The following example notebooks are available:

1. Train a model using high-level pipelines
2. Train a model and perform a backtest
3. Train a model and make a forecast
4. Split net load into components using DAZLs
5. Obtain derived features
6. Analyzing perturbed inputs

• Instructions
• License
• Licenses third-party libraries
• Contributing
• Contact

Install: pip install -r requirements.txt

Run: jupyter notebook

This project is licensed under the Mozilla Public License, version 2.0 - see LICENSE for details.

This project includes third-party libraries, which are licensed under their own respective Open-Source licenses. SPDX-License-Identifier headers are used to show which license is applicable. The concerning license files can be found in the LICENSES directory.

Please read CODE_OF_CONDUCT.md, CONTRIBUTING.md and PROJECT_GOVERNANACE.md for details on the process for submitting pull requests to us.

Please read SUPPORT.md for how to connect and get into contact with the OpenSTEF project