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The Mathematics of Machine Learning

Lectures on Supervised Methods and Beyond
Buch | Softcover
X, 200 Seiten
2024
De Gruyter (Verlag)
978-3-11-128847-5 (ISBN)
CHF 89,95 inkl. MwSt

This book is an introduction to machine learning, with a strong focus on the mathematics behind the standard algorithms and techniques in the field, aimed at senior undergraduates and early graduate students of Mathematics.

There is a focus on well-known supervised machine learning algorithms, detailing the existing theory to provide some theoretical guarantees, featuring intuitive proofs and exposition of the material in a concise and precise manner. A broad set of topics is covered, giving an overview of the field. A summary of the topics covered is: statistical learning theory, approximation theory, linear models, kernel methods, Gaussian processes, deep neural networks, ensemble methods and unsupervised learning techniques, such as clustering and dimensionality reduction.

This book is suited for students who are interested in entering the field, by preparing them to master the standard tools in Machine Learning. The reader will be equipped to understand the main theoretical questions of the current research and to engage with the field.

Maria Han Veiga, University of Michigan, USA; François Gaston Ged, École Polytechnique Fédèrale de Lausanne, Switzerland.

Erscheinungsdatum
Reihe/Serie De Gruyter Textbook
Zusatzinfo 13 b/w and 26 col. ill.
Verlagsort Berlin/Boston
Sprache englisch
Maße 170 x 240 mm
Gewicht 356 g
Themenwelt Informatik Theorie / Studium Künstliche Intelligenz / Robotik
Mathematik / Informatik Mathematik Angewandte Mathematik
Schlagworte Analytic Functions • Complex Analysis • Complex Integration • Complex variables • Kernel-Methoden • Neuronale Netze • Statistisches Lernen • überwachtes Lernen
ISBN-10 3-11-128847-1 / 3111288471
ISBN-13 978-3-11-128847-5 / 9783111288475
Zustand Neuware
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