Abstract
Machine learning (ML) is a very practical field. Consequently, the theoreticalmathematical content of the course 185.A83 ”Machine Learning for Health Informatics” is kept to a minimum. It is hard to keep a consistent notation throughout
the class to cover the extremely wide variety of data, models and algorithms discussed in this course. Definitions, conventions and usage of one and the same
expression may be very different in mathematics and in computer science. This
short document outlines some of the used mathematical notations. Note that one
and the same symbol may have different meaning in different context
the class to cover the extremely wide variety of data, models and algorithms discussed in this course. Definitions, conventions and usage of one and the same
expression may be very different in mathematics and in computer science. This
short document outlines some of the used mathematical notations. Note that one
and the same symbol may have different meaning in different context
Originalsprache | englisch |
---|---|
Seitenumfang | 8 |
Publikationsstatus | Veröffentlicht - 7 Juli 2016 |
ASJC Scopus subject areas
- Artificial intelligence
Fields of Expertise
- Information, Communication & Computing
Treatment code (Nähere Zuordnung)
- Basic - Fundamental (Grundlagenforschung)