Machine learning is a subarea of artificial intelligence (AI). In the context of machine learning, IT systems are able to recognize patterns in data sets and documents, find solutions to complex problems and improve themselves independently. Since the system learns primarily from experience, high experience values, i.e. a large number of events, are a prerequisite for successful machine learning.

Furthermore, before a system can learn and develop solutions on its own, humans must provide the roadmap using algorithms and data. Rules are also given at the outset. From these algorithms and data, the respective system learns, creates its own independent program code and continuously develops it. Development is a complex and interactive process that must be run through several times before it can be launched. So the fact that humans only have to intervene once at the beginning is very rare in practice.

Among other things, Machine Learning makes it possible to find, extract and summarize data. Machine learning is also used to make predictions and calculate probabilities as well as to improve processes on the basis of recognized patterns.