Bernhard Vennemann: Catalogue data in Spring Semester 2020

Name Dr. Bernhard Vennemann
DepartmentMechanical and Process Engineering

151-0118-00LApplied Machine Learning for Engineers Restricted registration - show details
Number of participants limited to 40.
4 credits3GB. Vennemann
AbstractIntroduction to the most frequently used methods of machine learning, including regression, classification, dimensionality reduction and selected topics of deep learning, including artificial neural networks, convolutional neural networks, recurrent neural networks and autoencoders. This lecture has a strong practical focus with programming sessions.
ObjectiveAn understanding of the various tools within the machine learning landscape. Ability to select an appropriate method and to build, train and evaluate a model using Scikit-learn and Keras.
ContentData preprocessing, regression, classification, dimensionality reduction, artificial neural networks, convolutional neural networks, recurrent neural networks, autoencoders.
Lecture notesLecture notes will be distributed electronically.
Prerequisites / NoticeBasic knowledge of the Python programming language. This course is mainly targeted towards master-level students of mechanical or process engineering.