Applied Machine Learning for Anomaly Detection on Equipment

Workshop presented during AMLD2019 26.01.2019 in Lausanne

Original description is available at AMLD webpages.

The introductory slides are available in the slides folder of this repository.

Setup

To reproduce the virtual environment used for the workshop install pipenv and type:

pipenv install

Then you should be able to start a jupyter notebook and execute the notebook content.

Note

We are currently not providing access to Arundo Composer therefore you won't be able to follow the second part of the tutorial and deploy models to Arundo Fabric.

Data

The data used in this workshop was extracted from the Turbofan engine degradation simulation data set (dataset ID: "FD001").

Reference: Saxena, A., Goebel, K., Simon, D. and Eklund, N., 2008, October. Damage propagation modeling for aircraft engine run-to-failure simulation. In Prognostics and Health Management, 2008. PHM 2008. International Conference on (pp. 1-9). IEEE.

Questions? Suggestions?

If you have any questions about the presented content or would like to suggest ways we could improve this tutorial please reach out to us at support@arundo.com.