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Machine learning :
Machine learning : a first course for engineers and scientists
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- Lindholm, Andreas (författare)
- Annotell, Göteborg, Sweden
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- Wahlström, Niklas, 1984- (författare)
- Uppsala universitet,Avdelningen för systemteknik,Artificiell intelligens,Uppsala universitet, Sweden
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- Lindsten, Fredrik, 1984- (författare)
- Linköpings universitet,Statistik och maskininlärning,Tekniska fakulteten
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- Schön, Thomas B., Professor, 1977- (författare)
- Uppsala universitet,Avdelningen för systemteknik,Artificiell intelligens,Uppsala universitet, Sweden
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- Sumpter, David J. T. (bidragsgivare)
- Uppsala universitet,Avdelningen för systemteknik,Artificiell intelligens
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(creator_code:org_t)
- ISBN 9781108843607
- Cambridge, United Kingdom : Cambridge University Press, 2022
- Engelska 338 s.
- Relaterad länk:
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https://smlbook.org/
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https://libris.kb.se...
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https://urn.kb.se/re...
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Innehållsförteckning
Abstract
Recensioner
Ämnesord
Stäng
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- This book introduces machine learning for readers with some background in basic linear algebra, statistics, probability, and programming. In a coherent statistical framework it covers a selection of supervised machine learning methods, from the most fundamental (k-NN, decision trees, linear and logistic regression) to more advanced methods (deep neural networks, support vector machines, Gaussian processes, random forests and boosting), plus commonly-used unsupervised methods (generative modeling, k-means, PCA, autoencoders and generative adversarial networks). Careful explanations and pseudo-code are presented for all methods. The authors maintain a focus on the fundamentals by drawing connections between methods and discussing general concepts such as loss functions, maximum likelihood, the bias-variance decomposition, ensemble averaging, kernels and the Bayesian approach along with generally useful tools such as regularization, cross validation, evaluation metrics and optimization methods. The final chapters offer practical advice for solving real-world supervised machine learning problems and on ethical aspects of modern machine learning
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Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences (hsv//eng)
- NATURVETENSKAP -- Matematik -- Sannolikhetsteori och statistik (hsv//swe)
- NATURAL SCIENCES -- Mathematics -- Probability Theory and Statistics (hsv//eng)
Nyckelord
- Maskininlärning
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- bok (ämneskategori)
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