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Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning

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Machine Learning - A First Course for Engineers and Scientists (Hardcover) Loot Price: R1,624
Discovery Miles 16 240
Machine Learning - A First Course for Engineers and Scientists (Hardcover): Andreas Lindholm, Niklas Wahlstroem, Fredrik...

Machine Learning - A First Course for Engineers and Scientists (Hardcover)

Andreas Lindholm, Niklas Wahlstroem, Fredrik Lindsten, Thomas B. Schoen

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Loot Price R1,624 Discovery Miles 16 240 | Repayment Terms: R152 pm x 12*

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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.

General

Imprint: Cambridge UniversityPress
Country of origin: United Kingdom
Release date: March 2022
Authors: Andreas Lindholm • Niklas Wahlstroem • Fredrik Lindsten • Thomas B. Schoen
Dimensions: 259 x 182 x 20mm (L x W x T)
Format: Hardcover
Pages: 350
ISBN-13: 978-1-108-84360-7
Categories: Books > Computing & IT > General theory of computing > Mathematical theory of computation
Books > Computing & IT > Applications of computing > Signal processing
Books > Reference & Interdisciplinary > Communication studies > Information theory > General
Books > Science & Mathematics > Mathematics > Applied mathematics > Mathematical modelling
Books > Computing & IT > Applications of computing > Artificial intelligence > Machine learning
LSN: 1-108-84360-3
Barcode: 9781108843607

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