Workshop "Data analytics for engineering data using machine learning" – 2022

Data analytics for engineering data using machine learning

2022, Virtual (Microsoft Teams)

You can register here for planned workshops in 2022 (without obligation). We will then contact you as soon as possible with future workshop dates.

This two-day online workshop addresses the preparation, analysis and interpretation of numerical simulation data by machine learning methods. Besides the introduction of the most important concepts like clustering, dimensionality reduction, visualization and prediction, this course provides several practical hands-on tutorials using the python libraries numpy, scikit-learn and pytorch as well as the SCAI SimExplore.

Learning Outcomes

  • Basic knowledge on important machine learning methods to analyze numerical simulation data
  • Practical experience in applying these methods
     

Target audience

  • Researcher, developer and industrial end-users interested in new ways to analyze and visualize numerical simulation data
     

Agenda

Day 1

09:45-10:00 Drop in to the videoconference
10:00-13:00 Introduction to machine learning methods like clustering and dimensionality reduction by means of short practical exercises in python
13:00-14:00 Lunch break
14:00-17:00 Application of the methods from the previous session to numerical simulation data stemming from engineering applications with the help of the SCAI SimExplore

 

Day 2

09:45-10:00 Drop in to the videoconference
10:00-13:00 Introduction to prediction by deep learning methods together with hands-on exercises using the software library pyTorch
13:00-14:00 Lunch break
14:00-17:00 Introduction to interpretability of machine learning methods with the help of the examples from the previous session

 

Prerequisites

  • Preliminary experience with Python is required. Since Python is used, this tutorial can be used to learn the syntax
  • Preliminary experience in using Jupyter Notebook is also required