Machine Learning
by Abdelhamid Mellouk, Abdennacer Chebira
Publisher: InTech 2009
ISBN-13: 9789537619561
Number of pages: 450
Description:
Neural machine learning approaches, Hamiltonian neural networks, similarity discriminant analysis, machine learning methods for spoken dialogue simulation and optimization, linear subspace learning for facial expression analysis, 3d shape classification and retrieval, genetic network programming with reinforcement learning, heuristic dynamic programming, and more.
Download or read it online for free here:
Download link
(PDF)
Similar books
Machine Learning and Data Mining: Lecture Notes
by Aaron Hertzmann - University of Toronto
Contents: Introduction to Machine Learning; Linear Regression; Nonlinear Regression; Quadratics; Basic Probability Theory; Probability Density Functions; Estimation; Classification; Gradient Descent; Cross Validation; Bayesian Methods; and more.
(10485 views)
by Aaron Hertzmann - University of Toronto
Contents: Introduction to Machine Learning; Linear Regression; Nonlinear Regression; Quadratics; Basic Probability Theory; Probability Density Functions; Estimation; Classification; Gradient Descent; Cross Validation; Bayesian Methods; and more.
(10485 views)
A Survey of Statistical Network Models
by A. Goldenberg, A.X. Zheng, S.E. Fienberg, E.M. Airoldi - arXiv
We begin with the historical development of statistical network modeling and then we introduce some examples in the network literature. Our subsequent discussion focuses on prominent static and dynamic network models and their interconnections.
(9039 views)
by A. Goldenberg, A.X. Zheng, S.E. Fienberg, E.M. Airoldi - arXiv
We begin with the historical development of statistical network modeling and then we introduce some examples in the network literature. Our subsequent discussion focuses on prominent static and dynamic network models and their interconnections.
(9039 views)
The Hundred-Page Machine Learning Book
by Andriy Burkov
This is the first successful attempt to write an easy to read book on machine learning that isn't afraid of using math. It's also the first attempt to squeeze a wide range of machine learning topics in a systematic way and without loss in quality.
(9829 views)
by Andriy Burkov
This is the first successful attempt to write an easy to read book on machine learning that isn't afraid of using math. It's also the first attempt to squeeze a wide range of machine learning topics in a systematic way and without loss in quality.
(9829 views)
Machine Learning for Designers
by Patrick Hebron - O'Reilly Media
This book introduces you to contemporary machine learning systems and helps you integrate machine-learning capabilities into your user-facing designs. Patrick Hebron explains how machine-learning applications can affect the way you design websites.
(7496 views)
by Patrick Hebron - O'Reilly Media
This book introduces you to contemporary machine learning systems and helps you integrate machine-learning capabilities into your user-facing designs. Patrick Hebron explains how machine-learning applications can affect the way you design websites.
(7496 views)