This book presents machine learning models and algorithms to address big data classification problems. Existing machine learning techniques like the decision tree (a hierarchical approach), random for
This book discusses how to combine type-2 fuzzy sets and graphical models to solve a range of real-world pattern recognition problems such as speech recognition, handwritten Chinese character recognit
This book brings together important topics of current research in probabilistic graphical modeling, learning from data and probabilistic inference. Coverage includes such topics as the characterizatio
"The authors have written an enjoyable book - rigorous in the treatment of the mathematical background, but also enlivened by interesting and original historical and philosophical perspectives." -- Ma
This book provides a versatile and lucid treatment of classic as well as modern probability theory, while integrating them with core topics in statistical theory and also some key tools in machine lea
This Book discusses machine learning for model order reduction, which can be used in modern VLSI design to predict the behavior of an electronic circuit, via mathematical models that predict behavior.
This book addresses the theory and practice of using digital resources for contemporary learning, and how such resources can be designed, developed, and employed in a variety of learning activities an
This book covers the key ideas that link probability, statistics, and machine learning illustrated using Python modules in these areas. The entire text, including all the figures and n
Machine Learning Projects for .NET Developers shows you how to build smarter .NET applications that learn from data, using simple algorithms and techniques that can be applied to a wide range of real-
This book is a thorough introduction to the most important topics in data mining and machine learning. It begins with a detailed review of classical function estimation and proceeds with chapters on
The book covers tools in the study of online social networks such as machine learning techniques, clustering, and deep learning. A variety of theoretical aspects, application domains, and case studies
The aim of this volume entitled Digital Technologies: Sustainable Innovations for improving Teaching and Learning is to contribute in the global discussion on digital technologies as the means to fost
This book guides the adoption, design, development and expectation of future digital teaching and learning projects/programs in K12 schools. It provides a series of case studies and reports experience
This second edition focuses on audio, image and video data, the three main types of input that machines deal with when interacting with the real world. A set of appendices provides the reader with sel
Introducing Digital Communications into Your Medical Practice discusses how electronic medical records and personal health records now digitize patient information and make it accessible for review an
Digital Darwinism is a key challenge for all companies and brands. Not all companies and managers are aware of the challenges lying ahead. This book helps to identify the need for change and adaption
Offering sequenced guidance for non-specialists on how to reap the benefits of machine learning in medicine and healthcare, this text harnesses the power of cutting-edge computing to maximize the acce
This thesis discusses the privacy issues in speech-based applications such as biometric authentication, surveillance, and external speech processing services. Author Manas A. Pathak presents solutions
The objective of Document Analysis and Recognition (DAR) is to recognize the text and graphical components of a document and to extract information. This book is a collection of research papers and st
Introducing Digital Communications into Your Medical Practice discusses how electronic medical records and personal health records now digitize patient information and make it accessible for review a
The objective of Document Analysis and Recognition (DAR) is to recognize the text and graphical components of a document and to extract information. This book is a collection of research papers and st
This book focuses on the study of possible adaptive sampling mechanisms for haptic data compression aimed at applications like tele-operations and tele-surgery. Demonstrating that the selection of the
This book posits the idea that networked learning is the one new paradigm in learning theory that has resulted from the introduction of digital and networked technologies. It sets out, in a single vol
? This volume considers, and potentially rethinks and reorganizes how support for learning across working life can be best conceptualized, organized and enacted. The key focus for contributions t
This book focuses on how machine learning techniques can be used to analyze and make use of one particular category of behavioral biometrics known as the gait biometric. A comprehensive Ground Reactio
The aim of the conference is to present and discuss new methods, issues and challenges encountered in all parts of the complex process of gradual development and application of digital surface models.
??This book addresses the issues confronting educators in the integration of digital technologies into their teaching and their students’ learning. Such issues include a skepticism of the added value
The current book is the first publication of a complete overview of machine learning methodologies for the medical and health sector. It was written as a training companion and as a must-read, not onl
Digital games offer enormous potential for learning and engagement in mathematics ideas and processes. This volume offers multidisciplinary perspectives—of educators, cognitive scientists, psychologis
Presenting cutting-edge research papers from the CELDA 2012 conference, this collection offers multi-disciplinary, peer-reviewed coverage of the latest innovations in the use of digital systems and te
Changing student profiles and the increasing availability of mainstream and specialized learning technologies are stretching the traditional face-to-face models of teaching and learning in higher educ
This book describes efforts to improve subject-independent automated classification techniques using a better feature extraction method and a more efficient model of classification. It evaluates three
This book provides an overview of the major changes induced by hydrocarbons (HCs) affecting rocks and surface sediments and their implications for non-seismic exploration methods, particularly for mar
This book introduces context-aware computing, providing definitions, categories, characteristics, and context awareness itself and discussing its applications with a particular focus on smart learning
In this book, we put forward a holistic conceptual framework for implementing Scholarship of Learning and Teaching (SoLT) in higher education. Unlike previous SoLT studies, which usually focus on a sp
This book will synthesize the state of knowledge related to thinking and technology and will provide strategies for helping young people cultivate thinking skills required to navigate the new digital
This is the first textbook on a generally applicable control strategy for turbulence and other complex nonlinear systems. The approach of the book employs powerful methods of machine learning for opti
This brief is concerned with tempered stable distributions and their associated Levy processes. It is a good text for researchers interested in learning about tempered stable distributions. A tem
The work presents new approaches to Machine Learning for Cyber Physical Systems, experiences and visions. It contains some selected papersfrom the international Conference ML4CPS – Machine Learn
The book reports on a novel approach for holistically identifying the relevant state drivers of complex, multi-stage manufacturing systems. This approach is able to utilize complex, diverse and high-d
