Mathematik für Informatik und Data Science
Language: German
Published by Springer, Berlin|Springer Berlin Heidelberg|Springer Vieweg, 2024
- Softcover
- New
Condition: New
£ 38.90
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Dieses Buch liefert eine kompakte aber fundierte Darstellung der wichtigsten Gebiete der Mathematik fuer Informatik, die insbesondere fuer Data Science, Kuenstliche Intelligenz und Maschinelles Lernen notwendig sind. Inhaltlich gehoeren dazu Grundlagen zu Lo.
Seller Inventory # 1612336260
- Title
- Mathematik für Informatik und Data Science
- Author
- Knoblauch, Andreas
- Publisher
- Springer, Berlin|Springer Berlin Heidelberg|Springer Vieweg
- Publication year
- 2024
- Condition
- New
- Binding
- Soft cover
- Language
- German
- ISBN 10
- 3662694786
- ISBN 13
- 9783662694787
- Dimensions
- 2.7 x 24 x 17
- Series
- Book 8 of 8: Studienbücher Informatik
Dieses Buch liefert eine kompakte aber fundierte Darstellung der wichtigsten Gebiete der Mathematik für Informatik, die insbesondere für Data Science, Künstliche Intelligenz und Maschinelles Lernen notwendig sind. Inhaltlich gehören dazu Grundlagen zu Logik und Beweisen, ein- und mehrdimensionale Analysis mit Differential- und Integralrechnung, Lineare Algebra mit Vektor- und Matrixrechnung, linearen Gleichungssystemen, Koordinatentransformationen, Eigenvektoren sowie Wahrscheinlichkeitsrechnung mit Grundlagen der Kombinatorik, Statistik und Informationstheorie. Trotz der kompakten Darstellung werden alle Konzepte und Sätze sorgfältig eingeführt und bewiesen. Nichts soll vom Himmel fallen, sondern aus Axiomen und elementaren Prinzipien hergeleitet werden. Ziel ist es beim Studierenden das befriedigende Gefühl zu erzeugen, alles von Grund auf verstanden zu haben, und nichts nur „glauben“ zu müssen.
"Synopsis" may belong to another edition of this title.
About the Author
Andreas Knoblauch ist Professor für Informatik an der Hochschule Albstadt-Sigmaringen. Er unterrichtet dort in den Studiengängen Technische Informatik, IT-Security, Wirtschaftsinformatik, Systems Engineering und Data Science unter anderem Mathematik, Intelligente Systeme, Maschinelles Lernen und Mustererkennung. Daneben forscht er im Bereich Bildverarbeitung, Objekterkennung, Neuronale Netze, Neuromorphe Assoziativspeicher und Selbstreferentielles Autonomes Lernen.
"About the title" may belong to another edition of this title.
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