02070nam a2200337 4500 20260723110356.0 a|||||r|||| 00| 0 260723b |||||||| |||| 00| 0 spa d 9780262043793 CO-ViULL spa 23 006.31 A456 Alpaydin, Ethem 165255 Introduction to machine learning / Ethem Alpaydin. 4ª edición. Cambridge, Massachusetts : The MIT Press, 2020. 683 páginas : figuras ; 24 centímetros. rdacontent texto txt rdamedia sin mediación n rdacarrier volumen nc Adaptive computation and machine learning series Incluye referencias bibliográficas e índice. 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. Aprendizaje automático 165256 Inteligencia artificial Minería de datos 44500 Redes neuronales (informática) 165257 Aprendizaje supervisado 165258 Alpaydin, Ethem. 165255 ddc BK 48627 48627 0 0 ddc 0 0 0 001 001 GEN 2026-04-28 Librería Temis Compra 83000.00 0 006.31 A456 088965 2026-07-23 11:04:46 Ej.:1 2026-07-23 SIS BK 0 0 ddc 0 0 0 001 001 GEN 2026-04-28 Librería Temis Compra 83000.00 0 006.31 A456 088966 2026-07-23 11:04:00 Ej.:2 2026-07-23 SIS BK