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Machine Learning Books

You are currently browsing 1–10 of 94 new and published books in the subject of Machine Learning — sorted by publish date from newer books to older books.

For books that are not yet published; please browse forthcoming books.

New and Published Books

  1. Soft Computing and Its Applications, Volume One

    A Unified Engineering Concept

    By Kumar S. Ray

    This is volume 1 of the two-volume set Soft Computing and Its Applications. This volume explains the primary tools of soft computing as well as provides an abundance of working examples and detailed design studies. The book starts with coverage of fuzzy sets and fuzzy logic and their various...

    Published September 15th 2014 by Apple Academic Press

  2. Exploring Neural Networks with C#

    By Ryszard Tadeusiewicz, Rituparna Chaki, Nabendu Chaki

    The utility of artificial neural network models lies in the fact that they can be used to infer functions from observations—making them especially useful in applications where the complexity of data or tasks makes the design of such functions by hand impractical.Exploring Neural Networks with C#...

    Published September 1st 2014 by CRC Press

  3. Case Studies in Secure Computing

    Achievements and Trends

    Edited by Biju Issac, Nauman Israr

    In today’s age of wireless and mobile computing, network and computer security is paramount. Case Studies in Secure Computing: Achievements and Trends gathers the latest research from researchers who share their insights and best practices through illustrative case studies.This book examines the...

    Published August 28th 2014 by Auerbach Publications

  4. Soft Computing and Its Applications

    Volumes One and Two

    By Kumar S. Ray

    This two-volume set explains the primary tools of soft computing as well as provides an abundance of working examples and detailed design studies. The books start with coverage of fuzzy sets and fuzzy logic and their various approaches to fuzzy reasoning and go on to discuss several advanced...

    Published August 14th 2014 by Apple Academic Press

  5. Data Classification

    Algorithms and Applications

    Edited by Charu C. Aggarwal

    Series: Chapman & Hall/CRC Data Mining and Knowledge Discovery Series

    Comprehensive Coverage of the Entire Area of Classification Research on the problem of classification tends to be fragmented across such areas as pattern recognition, database, data mining, and machine learning. Addressing the work of these different communities in a unified way, Data...

    Published July 24th 2014 by Chapman and Hall/CRC

  6. Background Modeling and Foreground Detection for Video Surveillance

    Edited by Thierry Bouwmans, Fatih Porikli, Benjamin Höferlin, Antoine Vacavant

    Background modeling and foreground detection are important steps in video processing used to detect robustly moving objects in challenging environments. This requires effective methods for dealing with dynamic backgrounds and illumination changes as well as algorithms that must meet real-time and...

    Published July 24th 2014 by Chapman and Hall/CRC

  7. Bayesian Networks

    With Examples in R

    By Marco Scutari, Jean-Baptiste Denis

    Series: Chapman & Hall/CRC Texts in Statistical Science

    Understand the Foundations of Bayesian Networks—Core Properties and Definitions Explained Bayesian Networks: With Examples in R introduces Bayesian networks using a hands-on approach. Simple yet meaningful examples in R illustrate each step of the modeling process. The examples start from the...

    Published June 19th 2014 by Chapman and Hall/CRC

  8. Approximate Iterative Algorithms

    By Anthony Louis Almudevar

    Iterative algorithms often rely on approximate evaluation techniques, which may include statistical estimation, computer simulation or functional approximation. This volume presents methods for the study of approximate iterative algorithms, providing tools for the derivation of error bounds and...

    Published February 17th 2014 by CRC Press

  9. High Performance Programming for Soft Computing

    Edited by Oscar Humberto Montiel Ross, Roberto Sepulveda

    This book examines the present and future of soft computer techniques. It explains how to use the latest technological tools, such as multicore processors and graphics processing units, to implement highly efficient intelligent system methods using a general purpose computer....

    Published February 3rd 2014 by CRC Press

  10. Bayesian Programming

    By Pierre Bessiere, Emmanuel Mazer, Juan Manuel Ahuactzin, Kamel Mekhnacha

    Series: Chapman & Hall/CRC Machine Learning & Pattern Recognition

    Probability as an Alternative to Boolean LogicWhile logic is the mathematical foundation of rational reasoning and the fundamental principle of computing, it is restricted to problems where information is both complete and certain. However, many real-world problems, from financial investments to...

    Published December 19th 2013 by Chapman and Hall/CRC