Lecture Notes in Machine Learning
by Zdravko Markov
Publisher: Central Connecticut State University 2003
Number of pages: 65
Description:
Contents: Introduction; Concept learning; Languages for learning; Version space learning; Induction of Decision trees; Covering strategies; Searching the generalization / specialization graph; Inductive Logic Progrogramming; Unsupervised Learning; Explanation-based Learning.
Download or read it online for free here:
Download link
(340KB, PDF)
Similar books
A First Encounter with Machine Learning
by Max Welling - University of California Irvine
The book you see before you is meant for those starting out in the field of machine learning, who need a simple, intuitive explanation of some of the most useful algorithms that our field has to offer. A prelude to the more advanced text books.
(12182 views)
by Max Welling - University of California Irvine
The book you see before you is meant for those starting out in the field of machine learning, who need a simple, intuitive explanation of some of the most useful algorithms that our field has to offer. A prelude to the more advanced text books.
(12182 views)
The LION Way: Machine Learning plus Intelligent Optimization
by Roberto Battiti, Mauro Brunato - Lionsolver, Inc.
Learning and Intelligent Optimization (LION) is the combination of learning from data and optimization applied to solve complex problems. This book is about increasing the automation level and connecting data directly to decisions and actions.
(35560 views)
by Roberto Battiti, Mauro Brunato - Lionsolver, Inc.
Learning and Intelligent Optimization (LION) is the combination of learning from data and optimization applied to solve complex problems. This book is about increasing the automation level and connecting data directly to decisions and actions.
(35560 views)
Boosting: Foundations and Algorithms
by Robert E. Schapire, Yoav Freund - The MIT Press
Boosting is an approach to machine learning based on the idea of creating a highly accurate predictor by combining many weak and inaccurate 'rules of thumb'. A remarkably rich theory has evolved around boosting, with connections to a range of topics.
(6496 views)
by Robert E. Schapire, Yoav Freund - The MIT Press
Boosting is an approach to machine learning based on the idea of creating a highly accurate predictor by combining many weak and inaccurate 'rules of thumb'. A remarkably rich theory has evolved around boosting, with connections to a range of topics.
(6496 views)
Machine Learning
by Abdelhamid Mellouk, Abdennacer Chebira - InTech
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, and more.
(16234 views)
by Abdelhamid Mellouk, Abdennacer Chebira - InTech
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, and more.
(16234 views)