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)

Deep Learning

Post date: 16 Apr 2016
The Deep Learning textbook is a resource intended to help students and practitioners enter the field of machine learning in general and deep learning in particular.
Publisher: The MIT Press
Publication date: 18 Nov 2016
Document Type: Textbook
 
Deep Learning

Deep Learning

Post date: 16 Apr 2016
The Deep Learning textbook is a resource intended to help students and practitioners enter the field of machine learning in general and deep learning in particular.
Publisher: The MIT Press
Publication date: 18 Nov 2016
Document Type: Textbook


Deep Learning Tutorials

Post date: 29 Mar 2016
The tutorials presented here will introduce you to some of the most important deep learning algorithms and will also show you how to run them using Theano.
Publication date: 29 Mar 2016
 
Deep Learning Tutorials

Deep Learning Tutorials

Post date: 29 Mar 2016
The tutorials presented here will introduce you to some of the most important deep learning algorithms and will also show you how to run them using Theano.
Publication date: 29 Mar 2016


Foundations of Data Science

Post date: 29 Sep 2016
Provides the background needed for a modern theoretical course in computer science.
Publication date: 11 Apr 2014
Document Type: Textbook
 
Foundations of Data Science

Foundations of Data Science

Post date: 29 Sep 2016
Provides the background needed for a modern theoretical course in computer science.
Publication date: 11 Apr 2014
Document Type: Textbook


Foundations of Machine Learning, Second Edition

Post date: 05 Feb 2021
A new edition of a graduate-level machine learning textbook that focuses on the analysis and theory of algorithms.
Publisher: The MIT Press
Publication date: 25 Dec 2018
License: The MIT License (MIT)
Document Type: Textbook
 
Foundations of Machine Learning, Second Edition

Foundations of Machine Learning, Second Edition

Post date: 05 Feb 2021
A new edition of a graduate-level machine learning textbook that focuses on the analysis and theory of algorithms.
Publisher: The MIT Press
Publication date: 25 Dec 2018
License: The MIT License (MIT) Document Type: Textbook


Free and Open Machine Learning

Post date: 30 Jul 2020
This book describes an open machine learning architecture. Including key aspects that are involved for real business use. It focuses on FOSS machine learning software and open datasets.
Publisher: The Business Management Support Foundation
Publication date: 04 Jul 2020
License: Creative Commons Attribution-ShareAlike 4.0 International
Document Type: Book
 
Free and Open Machine Learning

Free and Open Machine Learning

Post date: 30 Jul 2020
This book describes an open machine learning architecture. Including key aspects that are involved for real business use. It focuses on FOSS machine learning software and open datasets.
Publisher: The Business Management Support Foundation
Publication date: 04 Jul 2020
License: Creative Commons Attribution-ShareAlike 4.0 International Document Type: Book


Gaussian Processes for Machine Learning

Post date: 04 Oct 2007
The book deals with the supervised-learning problem for both regression and classification, and includes detailed algorithms. Contains illustrative examples and exercises, and code and datasets are available on the Web.
Publisher: The MIT Press
Publication date: 31 Dec 2006
 
Gaussian Processes for Machine Learning

Gaussian Processes for Machine Learning

Post date: 04 Oct 2007
The book deals with the supervised-learning problem for both regression and classification, and includes detailed algorithms. Contains illustrative examples and exercises, and code and datasets are available on the Web.
Publisher: The MIT Press
Publication date: 31 Dec 2006


Introduction to Machine Learning

Post date: 19 Nov 2006
This book surveys many of the important topics in machine learning circa 1996. The intention was to pursue a middle ground between theory and practice. It is neither a handbook of practice nor a compendium of theoretical proofs.
Publication date: 01 Jan 2005
 
Introduction to Machine Learning

Introduction to Machine Learning

Post date: 19 Nov 2006
This book surveys many of the important topics in machine learning circa 1996. The intention was to pursue a middle ground between theory and practice. It is neither a handbook of practice nor a compendium of theoretical proofs.
Publication date: 01 Jan 2005


Introduction to Machine Learning

Post date: 02 Apr 2016
These lecture notes are used in an introductory course in Machine Learning at Purdue University. Strong background in Probability theory, Linear Algebra and Programming are a must.
Publisher: Cambridge University Press
Publication date: 01 Oct 2010
 
Introduction to Machine Learning

Introduction to Machine Learning

Post date: 02 Apr 2016
These lecture notes are used in an introductory course in Machine Learning at Purdue University. Strong background in Probability theory, Linear Algebra and Programming are a must.
Publisher: Cambridge University Press
Publication date: 01 Oct 2010


Introduction to Machine Learning

Post date: 29 May 2016
Class notes of Machine Learning course given at the Hebrew University of Jerusalem.
Publication date: 23 Apr 2009
 
Introduction to Machine Learning

Introduction to Machine Learning

Post date: 29 May 2016
Class notes of Machine Learning course given at the Hebrew University of Jerusalem.
Publication date: 23 Apr 2009


Lifelong Machine Learning

Post date: 22 Feb 2021
This book serves as an introductory text and survey to lifelong learning.
Publisher: Morgan & Claypool Publishers
Publication date: 01 Jan 2017
Document Type: Textbook
 
Lifelong Machine Learning

Lifelong Machine Learning

Post date: 22 Feb 2021
This book serves as an introductory text and survey to lifelong learning.
Publisher: Morgan & Claypool Publishers
Publication date: 01 Jan 2017
Document Type: Textbook


Machine Learning

Post date: 21 Apr 2016
A collection of 20 publications on Machine Learning.
Publisher: I-Tech Education and Publishing
Publication date: 01 Jan 2009
License: Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported
Document Type: Book
 
Machine Learning

Machine Learning

Post date: 21 Apr 2016
A collection of 20 publications on Machine Learning.
Publisher: I-Tech Education and Publishing
Publication date: 01 Jan 2009
License: Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported Document Type: Book


Machine Learning and Data Mining Lecture Notes

Post date: 05 Aug 2016
Lecture notes for CSC 411 Machine Learning and Data Mining course at the University of Toronto.
Publication date: 06 Feb 2012
Document Type: Lecture Notes
 
Machine Learning and Data Mining Lecture Notes

Machine Learning and Data Mining Lecture Notes

Post date: 05 Aug 2016
Lecture notes for CSC 411 Machine Learning and Data Mining course at the University of Toronto.
Publication date: 06 Feb 2012
Document Type: Lecture Notes


Machine Learning Yearning

Post date: 23 Feb 2021
This book will help you or your team making rapid progress while working on a machine learning application.
Publication date: 01 Jan 2018
Document Type: Book
 
Machine Learning Yearning

Machine Learning Yearning

Post date: 23 Feb 2021
This book will help you or your team making rapid progress while working on a machine learning application.
Publication date: 01 Jan 2018
Document Type: Book


Machine Learning, Neural and Statistical Classification

Post date: 25 Jan 2007
The aim of this book is to provide a review of different approaches to classification, compare their performance on a wide range of challenging data-sets, and draw conclusions on their applicability to realistic industrial problems.
Publisher: Ellis Horwood
Publication date: 17 Feb 1994
 
Machine Learning, Neural and Statistical Classification

Machine Learning, Neural and Statistical Classification

Post date: 25 Jan 2007
The aim of this book is to provide a review of different approaches to classification, compare their performance on a wide range of challenging data-sets, and draw conclusions on their applicability to realistic industrial problems.
Publisher: Ellis Horwood
Publication date: 17 Feb 1994


Numerical Algorithms: Methods for Computer Vision, Machine Learning, and Graphics

Post date: 19 Dec 2016
This textbook presents a new approach to numerical analysis for modern computer scientists and introduces numerical modeling and algorithmic design from a practical standpoint and provides insight into the theoretical tools needed to support these skills.
Publisher: A K Peters, Ltd.
Publication date: 13 Jul 2015
Document Type: Textbook
 
Numerical Algorithms: Methods for Computer Vision, Machine Learning, and Graphics

Numerical Algorithms: Methods for Computer Vision, Machine Learning, and Graphics

Post date: 19 Dec 2016
This textbook presents a new approach to numerical analysis for modern computer scientists and introduces numerical modeling and algorithmic design from a practical standpoint and provides insight into the theoretical tools needed to support these skills.
Publisher: A K Peters, Ltd.
Publication date: 13 Jul 2015
Document Type: Textbook


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