SériesAdaptive Computation And Machine Learning

19 Obras Popularidade 12,126 (589 Membros) 1,000 Livros 11 Resenhas 4.1
Bioinformatics: The Machine Learning Approach de Pierre Baldi 71 cópias, 1 resenha
Boosting: Foundations and Algorithms de Robert E. Schapire 24 cópias, 1 resenha
Causation, Prediction, and Search de Peter Spirtes 29 cópias, 1 resenha
Deep Learning de Ian Goodfellow 186 cópias
Elements of Causal Inference: Foundations and Learning Algorithms (Adaptive Computation and Machine Learning) de Jonas Peters 13 cópias
Foundations of Machine Learning de Mehryar Mohri 42 cópias, 1 resenha
Gaussian Processes for Machine Learning de Carl Edward Rasmussen 54 cópias, 1 resenha
Graphical Models for Machine Learning and Digital Communication de Brendan J. Frey 11 cópias
Introduction to Machine Learning de Ethem Alpaydin 103 cópias
Introduction to Statistical Relational Learning de Lise Getoor 18 cópias, 2 resenhas
Learning in Graphical Models de Michael I. Jordan 23 cópias
Learning Kernel Classifiers: Theory and Algorithms de Ralf Herbrich 14 cópias, 1 resenha
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond de Bernhard Schölkopf 48 cópias
Machine Learning in Non-Stationary Environments: Introduction to Covariate Shift Adaptation (Adaptive Computation and Machine Learning series) de Masashi Sugiyama 3 cópias
Machine Learning: A Probabilistic Perspective de Kevin P. Murphy 102 cópias
The Minimum Description Length Principle de Peter D. Grünwald 18 cópias, 1 resenha
Principles of Data Mining de David J. Hand 83 cópias
Reinforcement Learning: An Introduction de Richard S. Sutton 131 cópias, 1 resenha
Semi-Supervised Learning de Olivier Chapelle 19 cópias, 1 resenha

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