The mathematics of machine learning: lectures on supervised methods and beyond
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, detai...
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| Main Authors: | , |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Berlin ; Boston
De Gruyter
[2024]
© 2024 |
| Series: | De Gruyter Textbook
|
| Subjects: | |
| Online Access: | DE-1043 DE-1046 DE-858 DE-898 DE-859 DE-860 DE-91 DE-703 DE-20 DE-739 Volltext |
| Summary: | 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 |
| Physical Description: | 1 Online-Ressource (IX, 199 Seiten) Illustrationen, Diagramme |
| ISBN: | 9783111288994 9783111289816 |
| DOI: | 10.1515/9783111288994 |
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| spelling | Han Veiga, Maria Verfasser (DE-588)1332666396 aut The mathematics of machine learning lectures on supervised methods and beyond Maria Han Veiga and François Gaston Ged Berlin ; Boston De Gruyter [2024] © 2024 1 Online-Ressource (IX, 199 Seiten) Illustrationen, Diagramme txt rdacontent c rdamedia cr rdacarrier De Gruyter Textbook 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 Kernel-Methoden Neuronale Netze Statistisches Lernen überwachtes Lernen MATHEMATICS / Applied bisacsh Angewandte Mathematik (DE-588)4142443-8 gnd rswk-swf Maschinelles Lernen (DE-588)4193754-5 gnd rswk-swf Maschinelles Lernen (DE-588)4193754-5 s Angewandte Mathematik (DE-588)4142443-8 s DE-604 Ged, François Verfasser (DE-588)1332667236 aut Erscheint auch als Druck-Ausgabe 978-3-11-128847-5 (DE-604)BV049748196 https://doi.org/10.1515/9783111288994 Verlag URL des Erstveröffentlichers Volltext |
| spellingShingle | Han Veiga, Maria Ged, François The mathematics of machine learning lectures on supervised methods and beyond Kernel-Methoden Neuronale Netze Statistisches Lernen überwachtes Lernen MATHEMATICS / Applied bisacsh Angewandte Mathematik (DE-588)4142443-8 gnd Maschinelles Lernen (DE-588)4193754-5 gnd |
| subject_GND | (DE-588)4142443-8 (DE-588)4193754-5 |
| title | The mathematics of machine learning lectures on supervised methods and beyond |
| title_auth | The mathematics of machine learning lectures on supervised methods and beyond |
| title_exact_search | The mathematics of machine learning lectures on supervised methods and beyond |
| title_full | The mathematics of machine learning lectures on supervised methods and beyond Maria Han Veiga and François Gaston Ged |
| title_fullStr | The mathematics of machine learning lectures on supervised methods and beyond Maria Han Veiga and François Gaston Ged |
| title_full_unstemmed | The mathematics of machine learning lectures on supervised methods and beyond Maria Han Veiga and François Gaston Ged |
| title_short | The mathematics of machine learning |
| title_sort | the mathematics of machine learning lectures on supervised methods and beyond |
| title_sub | lectures on supervised methods and beyond |
| topic | Kernel-Methoden Neuronale Netze Statistisches Lernen überwachtes Lernen MATHEMATICS / Applied bisacsh Angewandte Mathematik (DE-588)4142443-8 gnd Maschinelles Lernen (DE-588)4193754-5 gnd |
| topic_facet | Kernel-Methoden Neuronale Netze Statistisches Lernen überwachtes Lernen MATHEMATICS / Applied Angewandte Mathematik Maschinelles Lernen |
| url | https://doi.org/10.1515/9783111288994 |
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