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Machine Learning: A First Course for Engineers and Scientists - Lindholm, Andreas, and Wahlström, Niklas, and Lindsten, Fredrik
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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 ...

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Machine Learning: A First Course for Engineers and Scientists 2022, Cambridge University Press, Cambridge

ISBN-13: 9781108843607

Hardcover