Machine Learning for Engineers

Dr. Marcus J. Neuer has developed machine learning and explainable artificial intelligence for usable, profitable applications in various research and industry projects. He leads the research and development department at innoRIID GmbH and teaches at RWTH Aachen as well as the University of Applied Sciences for Business, FHDW. His algorithms are successfully used today in various products, including in the fields of nuclear safety and the process industry.

1 Introduction to Working with Data.- 2 Data as a Stochastic Process.- 3 Exploratory Analysis (Data Cleaning, Histograms, Principal Component Analysis, Mathematical Transformations).- 4 Fundamentals of Supervised and Unsupervised Learning Methods.- 5 Physics-Informed Learning Methods (Optimization Methods for Data Preprocessing, Integration of Transformatively-Enriched Data, Integration of Mathematical Models).- 6 Stochastic Learning Methods (Mixture-Density Networks, Credal Networks).- 7 Semantic Databases.- 8 Explainable, Trustworthy Artificial Intelligence.