TY  - JOUR
A1  - Janiesch, Christian
A1  - Zschech, Patrick
A1  - Heinrich, Kai
T1  - Machine learning and deep learning
JF  - Electronic Markets
N2  - Today, intelligent systems that offer artificial intelligence capabilities often rely on machine learning. Machine learning describes the capacity of systems to learn from problem-specific training data to automate the process of analytical model building and solve associated tasks. Deep learning is a machine learning concept based on artificial neural networks. For many applications, deep learning models outperform shallow machine learning models and traditional data analysis approaches. In this article, we summarize the fundamentals of machine learning and deep learning to generate a broader understanding of the methodical underpinning of current intelligent systems. In particular, we provide a conceptual distinction between relevant terms and concepts, explain the process of automated analytical model building through machine learning and deep learning, and discuss the challenges that arise when implementing such intelligent systems in the field of electronic markets and networked business. These naturally go beyond technological aspects and highlight issues in human-machine interaction and artificial intelligence servitization.
KW  - analytical model building
KW  - machine learning
KW  - deep learning
KW  - artificial intelligence
KW  - artificial neural networks
Y1  - 2021
U6  - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:bvb:20-opus-270155
SN  - 1422-8890
VL  - 31
IS  - 3
ER  -