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.
All categoriesBooks under this sub-category (35 books)
Reinforcement Learning: An Introduction, Second Edition
Post date: 09 Jan 2017This 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
Publication date: 03 Apr 2018
License: Creative Commons Attribution-NonCommercial-NoDerivs 2.0 Generic
Document Type: Textbook
Reinforcement Learning: An Introduction, Second Edition
Post date: 09 Jan 2017This 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
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: 21 Apr 2016This handbook aims to present the statistical foundations of machine learning intended as the discipline which deals with the automatic design of models from data.
Statistical Foundations of Machine Learning, Second Edition
Post date: 21 Apr 2016This handbook aims to present the statistical foundations of machine learning intended as the discipline which deals with the automatic design of models from data.
The Elements of Statistical Learning: Data Mining, Inference, and Prediction.
Post date: 09 Apr 2016This 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.
The Elements of Statistical Learning: Data Mining, Inference, and Prediction.
Post date: 09 Apr 2016This 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.
Theory and Applications for Advanced Text Mining
Post date: 13 Jun 2016This book is composed of 9 chapters introducing advanced text mining techniques. They are various techniques from relation extraction to under or less resourced language.
Theory and Applications for Advanced Text Mining
Post date: 13 Jun 2016This book is composed of 9 chapters introducing advanced text mining techniques. They are various techniques from relation extraction to under or less resourced language.
Understanding Machine Learning: From Theory to Algorithms
Post date: 02 Feb 2016This 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.
Understanding Machine Learning: From Theory to Algorithms
Post date: 02 Feb 2016This 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.
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