Alpaydin, Ethem creator Alpaydin, Ethem. text 4ª edición. monographic spa

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683 páginas : figuras ; 24 centímetros. The book covers a broad array of topics not usually included in introductory machine learning texts, including supervised learning, Bayesian decision theory, parametric methods, semiparametric methods, nonparametric methods, multivariate analysis, hidden Markov models, reinforcement learning, kernel machines, graphical models, Bayesian estimation, and statistical testing. The fourth edition offers a new chapter on deep learning that discusses training, regularizing, and structuring deep neural networks such as convolutional and generative adversarial networks; new material in the chapter on reinforcement learning that covers the use of deep networks, the policy gradient methods, and deep reinforcement learning; new material in the chapter on multilayer perceptrons on autoencoders and the word2vec network; and discussion of a popular method of dimensionality reduction, t-SNE. New appendixes offer background material on linear algebra and optimization. Ethem Alpaydin. Incluye referencias bibliográficas e índice. Aprendizaje automático Inteligencia artificial Minería de datos Redes neuronales (informática) Aprendizaje supervisado 006.31 A456 9780262043793 CO-ViULL 260723 20260723110356.0