151-0118-00L  Applied Machine Learning for Engineers

SemesterSpring Semester 2020
LecturersB. Vennemann
Periodicitynon-recurring course
Language of instructionEnglish
CommentNumber of participants limited to 40.


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.