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 (39 books)

Pattern Recognition and Machine Learning

Post date: 28 Nov 2020
This textbook provides a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first-year PhD students, as well as researchers and practitioners.
Publisher: Springer-Verlag GmbH
Publication date: 17 Aug 2006
Document Type: Textbook
 
Pattern Recognition and Machine Learning

Pattern Recognition and Machine Learning

Post date: 28 Nov 2020
This textbook provides a comprehensive introduction to the fields of pattern recognition and machine learning. It is aimed at advanced undergraduates or first-year PhD students, as well as researchers and practitioners.
Publisher: Springer-Verlag GmbH
Publication date: 17 Aug 2006
Document Type: Textbook


Probabilistic Models in the Study of Language

Post date: 30 Nov 2016
This textbook covers the topic of using probabilistic models in scientific work on language ranging from experimental data analysis to corpus work to cognitive modeling.
Publication date: 06 Nov 2012
Document Type: Textbook
 
Probabilistic Models in the Study of Language

Probabilistic Models in the Study of Language

Post date: 30 Nov 2016
This textbook covers the topic of using probabilistic models in scientific work on language ranging from experimental data analysis to corpus work to cognitive modeling.
Publication date: 06 Nov 2012
Document Type: Textbook


Python Machine Learning Projects

Post date: 26 Jul 2020
This book of Python projects in machine learning tries to equip the developers of today and tomorrow with tools they can use to better understand, evaluate, and shape machine learning.
Publisher: DigitalOcean
Publication date: 02 May 2019
License: Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International
Document Type: Book
 
Python Machine Learning Projects

Python Machine Learning Projects

Post date: 26 Jul 2020
This book of Python projects in machine learning tries to equip the developers of today and tomorrow with tools they can use to better understand, evaluate, and shape machine learning.
Publisher: DigitalOcean
Publication date: 02 May 2019
License: Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International Document Type: Book


Reinforcement Learning

Post date: 21 Apr 2016
The first 11 chapters of this book describe and extend the scope of reinforcement learning. The remaining 11 chapters show that there is already wide usage in numerous fields.
 
Reinforcement Learning

Reinforcement Learning

Post date: 21 Apr 2016
The first 11 chapters of this book describe and extend the scope of reinforcement learning. The remaining 11 chapters show that there is already wide usage in numerous fields.

Reinforcement Learning: An Introduction, Second Edition

Post date: 09 Jan 2017
This textbook provides a clear and simple account of the key ideas and algorithms of reinforcement learning that is accessible to readers in all the related disciplines. Familiarity with elementary concepts of probability is required.
Publisher: The MIT Press
Publication date: 03 Apr 2018
License: Creative Commons Attribution-NonCommercial-NoDerivs 2.0 Generic
Document Type: Textbook
 
Reinforcement Learning: An Introduction, Second Edition

Reinforcement Learning: An Introduction, Second Edition

Post date: 09 Jan 2017
This textbook provides a clear and simple account of the key ideas and algorithms of reinforcement learning that is accessible to readers in all the related disciplines. Familiarity with elementary concepts of probability is required.
Publisher: The MIT Press
Publication date: 03 Apr 2018
License: Creative Commons Attribution-NonCommercial-NoDerivs 2.0 Generic Document Type: Textbook


Statistical Foundations of Machine Learning, Second Edition

Post date: 20 Apr 2016
This handbook aims to present the statistical foundations of machine learning intended as the discipline which deals with the automatic design of models from data.
Publisher: OTexts
Publication date: 08 Feb 2021
Document Type: Book
 
Statistical Foundations of Machine Learning, Second Edition

Statistical Foundations of Machine Learning, Second Edition

Post date: 20 Apr 2016
This handbook aims to present the statistical foundations of machine learning intended as the discipline which deals with the automatic design of models from data.
Publisher: OTexts
Publication date: 08 Feb 2021
Document Type: Book


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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