SerieAdaptive Computation And Machine Learning

19 Opere Popolarità 11,962 (746 Utenti) 1,310 Libri 11 Recensioni 4.1
StoriaEdizione
Bioinformatics: The Machine Learning Approach di Pierre Baldi 83 copie
Boosting: Foundations and Algorithms di Robert E. Schapire 26 copie, 1 recensione
Causation, Prediction, and Search di Peter Spirtes 36 copie, 1 recensione
Deep Learning di Ian Goodfellow 298 copie, 1 recensione
Elements of Causal Inference: Foundations and Learning Algorithms (Adaptive Computation and Machine Learning) di Jonas Peters 21 copie
Foundations of Machine Learning di Mehryar Mohri 56 copie, 1 recensione
Gaussian Processes for Machine Learning di Carl Edward Rasmussen 67 copie, 1 recensione
Graphical Models for Machine Learning and Digital Communication di Brendan J. Frey 14 copie
Introduction to Machine Learning di Ethem Alpaydin 120 copie
Introduction to Statistical Relational Learning di Lise Getoor 22 copie, 2 recensioni
Learning in Graphical Models di Michael I. Jordan 26 copie
Learning Kernel Classifiers: Theory and Algorithms di Ralf Herbrich 18 copie, 1 recensione
Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond di Bernhard Schölkopf 54 copie
Machine Learning in Non-Stationary Environments: Introduction to Covariate Shift Adaptation (Adaptive Computation and Machine Learning series) di Masashi Sugiyama 3 copie
Machine Learning: A Probabilistic Perspective di Kevin P. Murphy 138 copie
The Minimum Description Length Principle di Peter D. Grünwald 25 copie, 1 recensione
Principles of Data Mining di David J. Hand 86 copie
Reinforcement Learning: An Introduction di Richard S. Sutton 176 copie, 1 recensione
Semi-Supervised Learning di Olivier Chapelle 24 copie, 1 recensione

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