Machine Learning

Machine learning explores the study and construction of algorithms that can learn from and make predictions on data. Such algorithms operate by building a model from example inputs in order to make data-driven predictions or decisions, rather than following strictly static program instructions.

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Books under this sub-category (33 books)

The Elements of Statistical Learning: Data Mining, Inference, and Prediction.

Post date: 08 Apr 2016
This book descibes the important ideas of data mining, machine learning, and bioinformatics in a common conceptual framework. Topics include neural networks, support vector machines, classification trees and boosting.
Publisher: Springer-Verlag GmbH
Publication date: 01 Dec 2015
Document Type: Textbook
 
The Elements of Statistical Learning: Data Mining, Inference, and Prediction.

The Elements of Statistical Learning: Data Mining, Inference, and Prediction.

Post date: 08 Apr 2016
This book descibes the important ideas of data mining, machine learning, and bioinformatics in a common conceptual framework. Topics include neural networks, support vector machines, classification trees and boosting.
Publisher: Springer-Verlag GmbH
Publication date: 01 Dec 2015
Document Type: Textbook


Theory and Applications for Advanced Text Mining

Post date: 13 Jun 2016
This book is composed of 9 chapters introducing advanced text mining techniques. They are various techniques from relation extraction to under or less resourced language.
Publisher: InTech
Publication date: 21 Nov 2012
License: Creative Commons Attribution 3.0 Unported
 
Theory and Applications for Advanced Text Mining

Theory and Applications for Advanced Text Mining

Post date: 13 Jun 2016
This book is composed of 9 chapters introducing advanced text mining techniques. They are various techniques from relation extraction to under or less resourced language.
Publisher: InTech
Publication date: 21 Nov 2012
License: Creative Commons Attribution 3.0 Unported


Understanding Machine Learning: From Theory to Algorithms

Post date: 02 Feb 2016
This book introduces machine learning and the algorithmic paradigms it offers. Designed for advanced undergraduates or beginning graduates, and accessible to students and non-expert readers in statistics, computer science, mathematics and engineering.
Publisher: Cambridge University Press
Publication date: 31 Dec 2014
 
Understanding Machine Learning: From Theory to Algorithms

Understanding Machine Learning: From Theory to Algorithms

Post date: 02 Feb 2016
This book introduces machine learning and the algorithmic paradigms it offers. Designed for advanced undergraduates or beginning graduates, and accessible to students and non-expert readers in statistics, computer science, mathematics and engineering.
Publisher: Cambridge University Press
Publication date: 31 Dec 2014


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