A First Course in Machine Learning
A First Course in Machine Learning by Simon Rogers and Mark Girolami is the best introductory book for ML currently available. It combines rigor and precision with accessibility, starts from a detailed explanation of the basic foundations of Bayesian analysis in the simplest of settings, and goes all the way to the frontiers of the subject such as infinite mixture models, GPs, and MCMC.-Devdatt Dubhashi, Professor, Department of Computer Science and Engineering, Chalmers University, SwedenThis textbook manages to be easier to read than other comparable books in the subject while retaining all the rigorous treatment needed. The new chapters pu…
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Produktdetails
Weitere Autoren: Girolami, Mark
- ISBN: 978-1-4987-3854-5
- EAN: 9781498738545
- Produktnummer: 21578599
- Verlag: Taylor & Francis Ltd.
- Sprache: Englisch
- Erscheinungsjahr: 2016
- Seitenangabe: 427 S.
- Plattform: PDF
- Masse: 134'564 KB
- Auflage: 2. Auflage
- Abbildungen: 186 schwarz-weiße Abbildungen, 8 schwarz-weiße Tabellen
Über den Autor
Simon Rogers is a lecturer in the School of Computing Science at the University of Glasgow, where he teaches a masters-level machine learning course on which this book is based. Dr. Rogers is an active researcher in machine learning, particularly applied to problems in computational biology. His research interests include the analysis of metabolomic data and the application of probabilistic machine learning techniques in the field of human-computer interaction.Mark Girolami holds an honorary professorship in Computer Science at the University of Warwick, is an EPSRC Established Career Fellow (2012 - 2017) and previously an EPSRC Advanced Research Fellow (2007 - 2012). He is also honorary Professor of Statistics at University College London, is the Director of the EPSRC funded Research Network on Computational Statistics and Machine Learning and in 2011 was elected to the Fellowship of the Royal Society of Edinburgh when he was also awarded a Royal Society Wolfson Research
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