Graphical Models for Machine Learning and Digital Communication

The book focusses on how machine learning and Internet of Things (IoT) has empowered the advancement of information driven arrangements including key concepts and advancements. Ontologies that are use

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

Wan and Mak describe machine-learning approaches to determining automatically the location of a protein within a cell in order to facilitate drug discovery and drug design. The approaches exploit the

This book provides a significant contribution to the increasing conversation concerning the place of big data in education. Offering a multidisciplinary approach with a diversity of perspectives from international scholars and industry experts, chapter authors engage in both research- and industry-informed discussions and analyses on the place of big data in education, particularly as it pertains to large-scale and ongoing assessment practices moving into the digital space. This volume offers an innovative, practical, and international view of the future of current opportunities and challenges in education and the place of assessment in this context.

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

This modern treatment of computer vision focuses on learning and inference in probabilistic models as a unifying theme. It shows how to use training data to learn the relationships between the observed image data and the aspects of the world that we wish to estimate, such as the 3D structure or the object class, and how to exploit these relationships to make new inferences about the world from new image data. With minimal prerequisites, the book starts from the basics of probability and model fitting and works up to real examples that the reader can implement and modify to build useful vision systems. Primarily meant for advanced undergraduate and graduate students, the detailed methodological presentation will also be useful for practitioners of computer vision. • Covers cutting-edge techniques, including graph cuts, machine learning and multiple view geometry • A unified approach shows the common basis for solutions of important computer vision problems, such as camera calibration, f

This practical guide is intended for faculty and service-learning directors, combining the how-to information and rigorous intellectual framework that teachers seek. What distinguishes this volume is

Examine business problems and use a practical analytical approach to solve them by implementing predictive models and machine learning techniques using SAS and the R analytical language. This bo

?Hybrid System Identification helps readers to build mathematical models of dynamical systems switching between different operating modes, from their experimental observations. It provides an overview

Although service-learning and nursing would seem an obvious combination, nursing, as a profession within academic, research, and health-care organizations has only recently begun to embrace the true s

In Practical Machine Learning with H2O.ai, author Darren Cook introduces readers to H2O, an open-source machine learning package that is gaining popularity in the data science community. This concise

The digital age has driven the need to combine radio-frequency engineering experience with overall high-speed digital design, as well as the need for an overall understanding of system performance. In

Digital Literacy for Technical Communication is designed to help technical communicators make better sense of technology's impact on their work, so they can identify new ways to adapt, adjust, and ev

Digital Literacy for Technical Communication helps technical communicators make better sense of technology’s impact on their work, so they can identify new ways to adapt, adjust, and evolve, ful

Create AI applications in Python and lay the foundations for your career in data scienceKey FeaturesPractical examples that explain key machine learning algorithmsExplore neural networks in detail wit

A new collection of stories, including some that have never before been seen, from the New York Times best-selling author of the Silo trilogy Hugh Howey is known for crafting riveting and immersive pa

A new collection of stories, including some that have never before been seen, from the New York Times best-selling author of the Silo trilogy Hugh Howey is known for crafting riveting and immersive pa

In the age of data-driven problem-solving, applying sophisticated computational tools for explaining substantive phenomena is a valuable skill. Yet, application of methods assumes an understanding of the data, structure, and patterns that influence the broader research program. This Element offers researchers and teachers an introduction to clustering, which is a prominent class of unsupervised machine learning for exploring and understanding latent, non-random structure in data. A suite of widely used clustering techniques is covered in this Element, in addition to R code and real data to facilitate interaction with the concepts. Upon setting the stage for clustering, the following algorithms are detailed: agglomerative hierarchical clustering, k-means clustering, Gaussian mixture models, and at a higher-level, fuzzy C-means clustering, DBSCAN, and partitioning around medoids (k-medoids) clustering.

This volume compiles 11 essays by education researchers from Europe, North America, and Israel, who explore the integration of information and communication technologies into STEM (science, techno

The renowned communications theorist Robert Gallager brings his lucid writing style to the study of the fundamental system aspects of digital communication for a one-semester course for graduate students. With the clarity and insight that have characterized his teaching and earlier textbooks, he develops a simple framework and then combines this with careful proofs to help the reader understand modern systems and simplified models in an intuitive yet precise way. A strong narrative and links between theory and practice reinforce this concise, practical presentation. The book begins with data compression for arbitrary sources. Gallager then describes how to modulate the resulting binary data for transmission over wires, cables, optical fibers, and wireless channels. Analysis and intuitive interpretations are developed for channel noise models, followed by coverage of the principles of detection, coding, and decoding. The various concepts covered are brought together in a description of

Due to the rapid development of gaming technologies in recent years, there has been a surge of interest in the role that digital games can play in foreign and second language learning. Bringing together innovative research from an international team of contributors, this book provides a comprehensive overview of the use of digital games in computer-assisted language learning (CALL).The book firstly lays the theoretical foundations and outlines various rationales for using digital games, incorporating contemporary theories of second language acquisition. It also explores the development and impact of digital games designed specifically for language learning, giving due consideration to design principles, pedagogical requirements and student health. Chapters then draw on case studies from Europe and Japan to analyse in-game interaction, attitudes and participation in both institutional and out-of-classroom settings. Seamlessly combining theory with practical application, this book outlin