Hands-On IV

Machine Learning for Signal Processing

Date:
26.09.2022, 15:30 - 17:00
Duration:
90 minutes
Location:
H 0.07
Max Participants:
20
Info:
Requires own laptop with MathWorks account.

Abstract

In this workshop we will apply common machine learning techniques to predict the state of charge of a battery and to detect anomalies in a production process.

We will specifically use support vector machines and decision trees in MATLAB for regression and anomaly detection. The workshop will focus on the application of theses algorithms, and we will gain a basic understanding of the algorithms through visualizations. This workshop is for researchers who work with time series and sensor data. You should have solid programming skills in MATLAB or another high-level programming language such as Python or Julia. It will be beneficial if you already have a basic understanding of machine learning. For the workshop we will use MATLAB Online (you can use MATLAB desktop if you have it installed). You will need a laptop and a MathWorks account to participate fully. If you do not have a MathWorks account, please create one with your university email address here: https://www.mathworks.com/mwaccount/
If you have any questions, please reach out to Franziska: falbers@mathworks.com

Dr. Franziska Albers

Senior Customer Success Engineer @ MathWorks