Numeric Computation and Statistical Data Analysis on the Java Platform
Numeric Computation and Statistical Data Analysis on the Java Platform

Author: Sergei V. Chekanov

Publisher: Springer

Published: 2016-03-23

Total Pages: 635

ISBN-13: 3319285319

DOWNLOAD EBOOK

Numerical computation, knowledge discovery and statistical data analysis integrated with powerful 2D and 3D graphics for visualization are the key topics of this book. The Python code examples powered by the Java platform can easily be transformed to other programming languages, such as Java, Groovy, Ruby and BeanShell. This book equips the reader with a computational platform which, unlike other statistical programs, is not limited by a single programming language. The author focuses on practical programming aspects and covers a broad range of topics, from basic introduction to the Python language on the Java platform (Jython), to descriptive statistics, symbolic calculations, neural networks, non-linear regression analysis and many other data-mining topics. He discusses how to find regularities in real-world data, how to classify data, and how to process data for knowledge discoveries. The code snippets are so short that they easily fit into single pages. Numeric Computation and Statistical Data Analysis on the Java Platform is a great choice for those who want to learn how statistical data analysis can be done using popular programming languages, who want to integrate data analysis algorithms in full-scale applications, and deploy such calculations on the web pages or computational servers regardless of their operating system. It is an excellent reference for scientific computations to solve real-world problems using a comprehensive stack of open-source Java libraries included in the DataMelt (DMelt) project and will be appreciated by many data-analysis scientists, engineers and students.

The Oxford Handbook of Affective Computing
The Oxford Handbook of Affective Computing

Author: Rafael A. Calvo

Publisher: Oxford Library of Psychology

Published: 2015

Total Pages: 625

ISBN-13: 0199942234

DOWNLOAD EBOOK

"The Oxford Handbook of Affective Computing is a definitive reference in the burgeoning field of affective computing (AC), a multidisciplinary field encompassing computer science, engineering, psychology, education, neuroscience, and other disciplines. AC research explores how affective factors influence interactions between humans and technology, how affect sensing and affect generation techniques can inform our understanding of human affect, and on the design, implementation, and evaluation of systems involving affect at their core. The volume features 41 chapters and is divided into five sections: history and theory, detection, generation, methodologies, and applications. Section 1 begins with the making of AC and a historical review of the science of emotion. The following chapters discuss the theoretical underpinnings of AC from an interdisciplinary viewpoint. Section 2 examines affect detection or recognition, a commonly investigated area. Section 3 focuses on aspects of affect generation, including the synthesis of emotion and its expression via facial features, speech, postures, and gestures. Cultural issues are also discussed. Section 4 focuses on methodological issues in AC research, including data collection techniques, multimodal affect databases, formats for the representation of emotion, crowdsourcing techniques, machine learning approaches, affect elicitation techniques, useful AC tools, and ethical issues. Finally, Section 5 highlights applications of AC in such domains as formal and informal learning, games, robotics, virtual reality, autism research, health care, cyberpsychology, music, deception, reflective writing, and cyberpsychology. This compendium will prove suitable for use as a textbook and serve as a valuable resource for everyone with an interest in AC."--

Obtaining Value from Big Data for Service Delivery
Obtaining Value from Big Data for Service Delivery

Author: Stephen H. Kaisler

Publisher: Business Expert Press

Published: 2015-12-21

Total Pages: 130

ISBN-13: 1631572237

DOWNLOAD EBOOK

Big data is an emerging phenomenon that has enormous implications and impacts upon business strategy, profitability, and process improvements. All service systems generate big data these days, especially human-centered service systems. It has been characterized as the collection, analysis and use of data characterized by the five Vs: volume, velocity, variety, veracity, and value (of data). This booklet will help middle, senior, and executive managers to understand what big data is; how to recognize, collect, process, and analyze it; how to store and manage it; how to obtain useful information from it; and how to assess its contribution to operational, tactical, and strategic decision-making in service-oriented organizations.

Advances in Mobile Cloud Computing and Big Data in the 5G Era
Advances in Mobile Cloud Computing and Big Data in the 5G Era

Author: Constandinos X. Mavromoustakis

Publisher: Springer

Published: 2016-11-19

Total Pages: 381

ISBN-13: 3319451456

DOWNLOAD EBOOK

This book reports on the latest advances on the theories, practices, standards and strategies that are related to the modern technology paradigms, the Mobile Cloud computing (MCC) and Big Data, as the pillars and their association with the emerging 5G mobile networks. The book includes 15 rigorously refereed chapters written by leading international researchers, providing the readers with technical and scientific information about various aspects of Big Data and Mobile Cloud Computing, from basic concepts to advanced findings, reporting the state-of-the-art on Big Data management. It demonstrates and discusses methods and practices to improve multi-source Big Data manipulation techniques, as well as the integration of resources availability through the 3As (Anywhere, Anything, Anytime) paradigm, using the 5G access technologies.

Computational Statistics in Data Science
Computational Statistics in Data Science

Author: Richard A. Levine

Publisher: John Wiley & Sons

Published: 2022-03-23

Total Pages: 672

ISBN-13: 1119561086

DOWNLOAD EBOOK

Ein unverzichtbarer Leitfaden bei der Anwendung computergestützter Statistik in der modernen Datenwissenschaft In Computational Statistics in Data Science präsentiert ein Team aus bekannten Mathematikern und Statistikern eine fundierte Zusammenstellung von Konzepten, Theorien, Techniken und Praktiken der computergestützten Statistik für ein Publikum, das auf der Suche nach einem einzigen, umfassenden Referenzwerk für Statistik in der modernen Datenwissenschaft ist. Das Buch enthält etliche Kapitel zu den wesentlichen konkreten Bereichen der computergestützten Statistik, in denen modernste Techniken zeitgemäß und verständlich dargestellt werden. Darüber hinaus bietet Computational Statistics in Data Science einen kostenlosen Zugang zu den fertigen Einträgen im Online-Nachschlagewerk Wiley StatsRef: Statistics Reference Online. Außerdem erhalten die Leserinnen und Leser: * Eine gründliche Einführung in die computergestützte Statistik mit relevanten und verständlichen Informationen für Anwender und Forscher in verschiedenen datenintensiven Bereichen * Umfassende Erläuterungen zu aktuellen Themen in der Statistik, darunter Big Data, Datenstromverarbeitung, quantitative Visualisierung und Deep Learning Das Werk eignet sich perfekt für Forscher und Wissenschaftler sämtlicher Fachbereiche, die Techniken der computergestützten Statistik auf einem gehobenen oder fortgeschrittenen Niveau anwenden müssen. Zudem gehört Computational Statistics in Data Science in das Bücherregal von Wissenschaftlern, die sich mit der Erforschung und Entwicklung von Techniken der computergestützten Statistik und statistischen Grafiken beschäftigen.

Data Analytics for Business
Data Analytics for Business

Author: Fenio Annansingh

Publisher: Routledge

Published: 2022-04-20

Total Pages: 265

ISBN-13: 1000577902

DOWNLOAD EBOOK

Data analytics underpin our modern data-driven economy. This textbook explains the relevance of data analytics at the firm and industry levels, tracing the evolution and key components of the field, and showing how data analytics insights can be leveraged for business results. The first section of the text covers key topics such as data analytics tools, data mining, business intelligence, customer relationship management, and cybersecurity. The chapters then take an industry focus, exploring how data analytics can be used in particular settings to strengthen business decision-making. A range of sectors are examined, including financial services, accounting, marketing, sport, health care, retail, transport, and education. With industry case studies, clear definitions of terminology, and no background knowledge required, this text supports students in gaining a solid understanding of data analytics and its practical applications. PowerPoint slides, a test bank of questions, and an instructor’s manual are also provided as online supplements. This will be a valuable text for undergraduate level courses in data analytics, data mining, business intelligence, and related areas.

Digital Personality
Digital Personality

Author: Kuldeep Singh Kaswan

Publisher: CRC Press

Published: 2024-08-30

Total Pages: 440

ISBN-13: 1040126723

DOWNLOAD EBOOK

A computer that imbibes human characteristics is considered to have a digital personality. The character is akin to real-life human with his/her distinguishing characteristics such as history, morality, beliefs, abilities, looks, and sociocultural embeddings. It also contains stable personality characteristics; fluctuating emotional, cognitive, SOAR technology, and motivational states. Digital Personality focuses on the creation of systems and interfaces that can observe, sense, predict, adapt to, affect, comprehend, or simulate the following: character based on behavior and situation, behavior based on character and situation, or situation based on character and behavior. Character sensing and profiling, character-aware adaptive systems, and artificial characters are the three primary subfields in digital personality. Digital Personality has attracted the interest of academics from a wide range of disciplines, including psychology, human-computer interaction, and character modeling. It is expected to expand quickly as technology and computer systems become more and more intertwined into our daily lives. Digital Personality is expected to draw at least as much attention as Affective Computing. The goal of affective computing is to enable computers to comprehend both spoken and nonverbal messages from people, use implicit body language, gaze, speech tones, and facial expressions, etc. to infer the emotional state and then reply appropriately or even show affect through interaction modalities. More natural and seamless human-computer connection would be the larger objective. Users will benefit from a more individualized experience as a result. Additionally, this will affect how well the user performs since they will have the assistance of the robots to do their jobs quickly and effectively. This book provides an overview of the character dimensions and how technology is aiding this area of study. It offers a fresh portrayal of character from several angles. It also discusses the applications of this new field of study.

Big Data Computing
Big Data Computing

Author: Vivek Kale

Publisher: CRC Press

Published: 2016-11-25

Total Pages: 651

ISBN-13: 1315354020

DOWNLOAD EBOOK

This book unravels the mystery of Big Data computing and its power to transform business operations. The approach it uses will be helpful to any professional who must present a case for realizing Big Data computing solutions or to those who could be involved in a Big Data computing project. It provides a framework that enables business and technical managers to make optimal decisions necessary for the successful migration to Big Data computing environments and applications within their organizations.

Predictive Analytics using R
Predictive Analytics using R

Author: Jeffrey Strickland

Publisher: Lulu.com

Published: 2015-01-16

Total Pages: 554

ISBN-13: 131284101X

DOWNLOAD EBOOK

This book is about predictive analytics. Yet, each chapter could easily be handled by an entire volume of its own. So one might think of this a survey of predictive modeling. A predictive model is a statistical model or machine learning model used to predict future behavior based on past behavior. In order to use this book, one should have a basic understanding of mathematical statistics - it is an advanced book. Some theoretical foundations are laid out but not proven, but references are provided for additional coverage. Every chapter culminates in an example using R. R is a free software environment for statistical computing and graphics. You may download R, from a preferred CRAN mirror at http: //www.r-project.org/. The book is organized so that statistical models are presented first (hopefully in a logical order), followed by machine learning models, and then applications: uplift modeling and time series. One could use this a textbook with problem solving in R-but there are no "by-hand" exercises.

Data Analytics Using Open-Source Tools
Data Analytics Using Open-Source Tools

Author: Jeffrey Strickland

Publisher: Lulu.com

Published: 2016-07-20

Total Pages: 708

ISBN-13: 1365270416

DOWNLOAD EBOOK

This book is about using open-source tools in data analytics. The book covers several subjects, including descriptive and predictive modeling, gradient boosting, cluster modeling, logistic regression, and artificial neural networks, among other topics.