List of all posted books
So far we have a total of 1245 books
Statistical Learning with Sparsity: The Lasso and Generalizations
Post date: 10 Apr 2016The explosion in computation and information technology has brought vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. This book descibes the important ideas in these areas in a common conceptual framework.
Publication date: 07 May 2015
Statistical Learning with Sparsity: The Lasso and Generalizations
Post date: 10 Apr 2016The explosion in computation and information technology has brought vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. This book descibes the important ideas in these areas in a common conceptual framework.
Publication date: 07 May 2015
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Post date: 10 Apr 2016
In this in-depth report, data scientist DJ Patil explains the skills,perspectives, tools and processes that position data science teams for success.
In this in-depth report, data scientist DJ Patil explains the skills,perspectives, tools and processes that position data science teams for success.
Post date: 10 Apr 2016In this in-depth report, data scientist DJ Patil explains the skills,perspectives, tools and processes that position data science teams for success.
The Promise and Peril of Big Data
Post date: 10 Apr 2016This book explores the positive aspects and the social perils that arise when the ever-rising floods of data being generated by mobile networking, cloud computing and other new technologies meets continued innovations in advanced correlation techniques.
Publisher:
The Aspen Institute
Publication date: 31 Jan 2010
License: Creative Commons Attribution-NonCommercial 3.0 United States
Publication date: 31 Jan 2010
License: Creative Commons Attribution-NonCommercial 3.0 United States
The Promise and Peril of Big Data
Post date: 10 Apr 2016This book explores the positive aspects and the social perils that arise when the ever-rising floods of data being generated by mobile networking, cloud computing and other new technologies meets continued innovations in advanced correlation techniques.
Publisher:
The Aspen Institute
Publication date: 31 Jan 2010
License: Creative Commons Attribution-NonCommercial 3.0 United States
Publication date: 31 Jan 2010
License: Creative Commons Attribution-NonCommercial 3.0 United States
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.
An Introduction to Statistical Learning with Applications in R
Post date: 08 Apr 2016An introduction to statistical learning methods, this book contains a number of R labs with detailed explanations on how to implement the various methods in real life settings.
An Introduction to Statistical Learning with Applications in R
Post date: 08 Apr 2016An introduction to statistical learning methods, this book contains a number of R labs with detailed explanations on how to implement the various methods in real life settings.
Spring by Example (Version 1.5)
Post date: 07 Apr 2016This book shows Java programmers how to leverage any part of the Spring framework to build applications that are easier to code, easier to test, and easier to manage.
Publication date: 31 Dec 2015
Spring by Example (Version 1.5)
Post date: 07 Apr 2016This book shows Java programmers how to leverage any part of the Spring framework to build applications that are easier to code, easier to test, and easier to manage.
Publication date: 31 Dec 2015
Linear Algebra, Theory and Applications
Post date: 07 Apr 2016This is a book on linear algebra and matrix theory. It is assumed that the reader has had some exposure to linear algebra and calculus.
Publisher:
Textbook Equity LLC
Publication date: 29 Jan 2012
License: Creative Commons Attribution 3.0 Unported
Publication date: 29 Jan 2012
License: Creative Commons Attribution 3.0 Unported
Linear Algebra, Theory and Applications
Post date: 07 Apr 2016This is a book on linear algebra and matrix theory. It is assumed that the reader has had some exposure to linear algebra and calculus.
Publisher:
Textbook Equity LLC
Publication date: 29 Jan 2012
License: Creative Commons Attribution 3.0 Unported
Publication date: 29 Jan 2012
License: Creative Commons Attribution 3.0 Unported
Non-Programmer's Tutorial for Python 3
Post date: 06 Apr 2016A conversion of Non-Programmer's Tutorial for Python 2.6, this tutorial is designed to be an introduction to the Python programming language for someone with no programming experience.
Non-Programmer's Tutorial for Python 3
Post date: 06 Apr 2016A conversion of Non-Programmer's Tutorial for Python 2.6, this tutorial is designed to be an introduction to the Python programming language for someone with no programming experience.
Publication date: 14 Jan 2016
License: Creative Commons Attribution-ShareAlike 3.0 Unported
License: Creative Commons Attribution-ShareAlike 3.0 Unported
Non-Programmer's Tutorial for Python 2.6
Post date: 06 Apr 2016A tutorial designed to be a introduction to the Python programming language for someone with no programming experience.
Non-Programmer's Tutorial for Python 2.6
Post date: 06 Apr 2016A tutorial designed to be a introduction to the Python programming language for someone with no programming experience.
Publication date: 05 Sep 2011
License: Creative Commons Attribution-ShareAlike 3.0 Unported
License: Creative Commons Attribution-ShareAlike 3.0 Unported
How to be a Programmer: Community Version
Post date: 05 Apr 2016This essay attempts to summarize what good programmer must do to make a software system that succeeds for both the customer and myriad colleagues for whom he is partially responsible.
How to be a Programmer: Community Version
Post date: 05 Apr 2016This essay attempts to summarize what good programmer must do to make a software system that succeeds for both the customer and myriad colleagues for whom he is partially responsible.
Publication date: 01 Jan 2016
License: Creative Commons Attribution-ShareAlike 4.0 International
License: Creative Commons Attribution-ShareAlike 4.0 International
C# Programming Yellow Book, The "Bananas" Edition
Post date: 05 Apr 2016An introduction to computer programming using C# language used by the Department of Computer Science in the University of Hull as the basis of the First Year programming course.
Publication date: 07 Sep 2015
C# Programming Yellow Book, The "Bananas" Edition
Post date: 05 Apr 2016An introduction to computer programming using C# language used by the Department of Computer Science in the University of Hull as the basis of the First Year programming course.
Publication date: 07 Sep 2015
Introduction to Design Patterns in C++ with Qt, Second Edition
Post date: 04 Apr 2016Teaches C++ "the Qt way," with an emphasis on design patterns and reuse of open source libraries and tools.
Introduction to Design Patterns in C++ with Qt, Second Edition
Post date: 04 Apr 2016Teaches C++ "the Qt way," with an emphasis on design patterns and reuse of open source libraries and tools.
Ada Distilled for Ada 2005: An Introduction to Ada Programming for Experienced Computer Programmers
Post date: 04 Apr 2016This book is aimed at experienced programmers who want to learn Ada at the programming level.
Ada Distilled for Ada 2005: An Introduction to Ada Programming for Experienced Computer Programmers
Post date: 04 Apr 2016This book is aimed at experienced programmers who want to learn Ada at the programming level.
Publication date: 01 Jan 2011
License: Standard Copyright License
License: Standard Copyright License
Post date: 03 Apr 2016
A set of introductory materials that covers most major aspects of modern machine learning (supervised learning, unsupervised learning, large margin methods, probabilistic modeling, learning theory, etc.).
A set of introductory materials that covers most major aspects of modern machine learning (supervised learning, unsupervised learning, large margin methods, probabilistic modeling, learning theory, etc.).
Publication date: 01 Sep 2015
Post date: 03 Apr 2016A set of introductory materials that covers most major aspects of modern machine learning (supervised learning, unsupervised learning, large margin methods, probabilistic modeling, learning theory, etc.).
Publication date: 01 Sep 2015
Introduction to Machine Learning
Post date: 03 Apr 2016These 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.
Introduction to Machine Learning
Post date: 03 Apr 2016These 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.
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