Download or read book Artificial Intelligence written by Sandeep Reddy and published by CRC Press. This book was released on 2020-12-02 with total page 287 pages. Available in PDF, EPUB and Kindle. Book excerpt: The rediscovery of the potential of artificial intelligence (AI) to improve healthcare delivery and patient outcomes has led to an increasing application of AI techniques such as deep learning, computer vision, natural language processing, and robotics in the healthcare domain. Many governments and health authorities have prioritized the application of AI in the delivery of healthcare. Also, technological giants and leading universities have established teams dedicated to the application of AI in medicine. These trends will mean an expanded role for AI in the provision of healthcare. Yet, there is an incomplete understanding of what AI is and its potential for use in healthcare. This book discusses the different types of AI applicable to healthcare and their application in medicine, population health, genomics, healthcare administration, and delivery. Readers, especially healthcare professionals and managers, will find the book useful to understand the different types of AI and how they are relevant to healthcare delivery. The book provides examples of AI being applied in medicine, population health, genomics, healthcare administration, and delivery and how they can commence applying AI in their health services. Researchers and technology professionals will also find the book useful to note current trends in the application of AI in healthcare and initiate their own projects to enable the application of AI in healthcare/medical domains.
Download or read book IBM SPSS Modeler Essentials written by Keith McCormick and published by Packt Publishing Ltd. This book was released on 2017-12-26 with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt: Get to grips with the fundamentals of data mining and predictive analytics with IBM SPSS Modeler About This Book Get up–and-running with IBM SPSS Modeler without going into too much depth. Identify interesting relationships within your data and build effective data mining and predictive analytics solutions A quick, easy–to-follow guide to give you a fundamental understanding of SPSS Modeler, written by the best in the business Who This Book Is For This book is ideal for those who are new to SPSS Modeler and want to start using it as quickly as possible, without going into too much detail. An understanding of basic data mining concepts will be helpful, to get the best out of the book. What You Will Learn Understand the basics of data mining and familiarize yourself with Modeler's visual programming interface Import data into Modeler and learn how to properly declare metadata Obtain summary statistics and audit the quality of your data Prepare data for modeling by selecting and sorting cases, identifying and removing duplicates, combining data files, and modifying and creating fields Assess simple relationships using various statistical and graphing techniques Get an overview of the different types of models available in Modeler Build a decision tree model and assess its results Score new data and export predictions In Detail IBM SPSS Modeler allows users to quickly and efficiently use predictive analytics and gain insights from your data. With almost 25 years of history, Modeler is the most established and comprehensive Data Mining workbench available. Since it is popular in corporate settings, widely available in university settings, and highly compatible with all the latest technologies, it is the perfect way to start your Data Science and Machine Learning journey. This book takes a detailed, step-by-step approach to introducing data mining using the de facto standard process, CRISP-DM, and Modeler's easy to learn “visual programming” style. You will learn how to read data into Modeler, assess data quality, prepare your data for modeling, find interesting patterns and relationships within your data, and export your predictions. Using a single case study throughout, this intentionally short and focused book sticks to the essentials. The authors have drawn upon their decades of teaching thousands of new users, to choose those aspects of Modeler that you should learn first, so that you get off to a good start using proven best practices. This book provides an overview of various popular data modeling techniques and presents a detailed case study of how to use CHAID, a decision tree model. Assessing a model's performance is as important as building it; this book will also show you how to do that. Finally, you will see how you can score new data and export your predictions. By the end of this book, you will have a firm understanding of the basics of data mining and how to effectively use Modeler to build predictive models. Style and approach This book empowers users to build practical & accurate predictive models quickly and intuitively. With the support of the advanced analytics users can discover hidden patterns and trends.This will help users to understand the factors that influence them, enabling you to take advantage of business opportunities and mitigate risks.
Download or read book Data Mining written by Ian H. Witten and published by Elsevier. This book was released on 2005-07-13 with total page 558 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Mining, Second Edition, describes data mining techniques and shows how they work. The book is a major revision of the first edition that appeared in 1999. While the basic core remains the same, it has been updated to reflect the changes that have taken place over five years, and now has nearly double the references. The highlights of this new edition include thirty new technique sections; an enhanced Weka machine learning workbench, which now features an interactive interface; comprehensive information on neural networks; a new section on Bayesian networks; and much more. This text is designed for information systems practitioners, programmers, consultants, developers, information technology managers, specification writers as well as professors and students of graduate-level data mining and machine learning courses. - Algorithmic methods at the heart of successful data mining—including tried and true techniques as well as leading edge methods - Performance improvement techniques that work by transforming the input or output
Download or read book Data Mining with IBM SPSS Modeler IBM SPSS Clementine written by César Pérez and published by Createspace Independent Pub. This book was released on 2013-06-14 with total page 242 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the most common techniques used in data mining in a simple and easy to understand through one of the most common software solutions from among those existing in the market, in particular, IBM SPSS CLEMENTINE whose current name is IBM SPSS MODELER. Pursued as initial aim clarifying the applications concerning methods traditionally rated as difficult or dull. It seeks to present applications in data mining without having to manage high mathematical developments or complicated theoretical algorithms, which is the most common reason for the difficulties in understanding and implementation of this matter. Today data mining is used in different fields of science. Noteworthy applications in banking, and financial analysis of markets and trade, insurance and private health, in education, in industrial processes, in medicine, biology and bioengineering, telecommunications and in many other areas. Essentials to get started in data mining, regardless of the field in which it is applied, is the understanding of own concepts, task that does not require nor much less the domain of scientific apparatus involved in the matter. Later, when either necessary operative advanced, computer programs allow the results without having to decipher the mathematical development of the algorithms that are under the procedures. This book describes the simplest possible data mining concepts, so that they are understandable by readers with different training. The chapters begin describing the techniques in affordable language and then presenting the way to treat them through practical applications. An important part of each chapter are case studies completely resolved, including the interpretation of the results, which is precisely the most important thing in any matter with which they work. The book begins with an introduction to mining data and its phases. In successive chapters develop the initial phases (selection of information, data exploration, data cleansing, transformation of data, etc.). Subsequently elaborates on specific data mining, both predictive and descriptive techniques. Predictive techniques covers all models of regression, discriminant analysis, decision trees, neural networks and other techniques based on models. The descriptive techniques vary dimension reduction techniques, techniques of classification and segmentation (clustering), and exploratory data analysis techniques.
Download or read book Introducing Machine Learning written by Dino Esposito and published by Microsoft Press. This book was released on 2020-01-31 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: Master machine learning concepts and develop real-world solutions Machine learning offers immense opportunities, and Introducing Machine Learning delivers practical knowledge to make the most of them. Dino and Francesco Esposito start with a quick overview of the foundations of artificial intelligence and the basic steps of any machine learning project. Next, they introduce Microsoft’s powerful ML.NET library, including capabilities for data processing, training, and evaluation. They present families of algorithms that can be trained to solve real-life problems, as well as deep learning techniques utilizing neural networks. The authors conclude by introducing valuable runtime services available through the Azure cloud platform and consider the long-term business vision for machine learning. · 14-time Microsoft MVP Dino Esposito and Francesco Esposito help you · Explore what’s known about how humans learn and how intelligent software is built · Discover which problems machine learning can address · Understand the machine learning pipeline: the steps leading to a deliverable model · Use AutoML to automatically select the best pipeline for any problem and dataset · Master ML.NET, implement its pipeline, and apply its tasks and algorithms · Explore the mathematical foundations of machine learning · Make predictions, improve decision-making, and apply probabilistic methods · Group data via classification and clustering · Learn the fundamentals of deep learning, including neural network design · Leverage AI cloud services to build better real-world solutions faster About This Book · For professionals who want to build machine learning applications: both developers who need data science skills and data scientists who need relevant programming skills · Includes examples of machine learning coding scenarios built using the ML.NET library
Download or read book Commercial Data Mining written by David Nettleton and published by Elsevier. This book was released on 2014-01-29 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: Whether you are brand new to data mining or working on your tenth predictive analytics project, Commercial Data Mining will be there for you as an accessible reference outlining the entire process and related themes. In this book, you'll learn that your organization does not need a huge volume of data or a Fortune 500 budget to generate business using existing information assets. Expert author David Nettleton guides you through the process from beginning to end and covers everything from business objectives to data sources, and selection to analysis and predictive modeling. Commercial Data Mining includes case studies and practical examples from Nettleton's more than 20 years of commercial experience. Real-world cases covering customer loyalty, cross-selling, and audience prediction in industries including insurance, banking, and media illustrate the concepts and techniques explained throughout the book. - Illustrates cost-benefit evaluation of potential projects - Includes vendor-agnostic advice on what to look for in off-the-shelf solutions as well as tips on building your own data mining tools - Approachable reference can be read from cover to cover by readers of all experience levels - Includes practical examples and case studies as well as actionable business insights from author's own experience
Download or read book Software Quality Engineering written by Jeff Tian and published by John Wiley & Sons. This book was released on 2005-05-20 with total page 440 pages. Available in PDF, EPUB and Kindle. Book excerpt: The one resource needed to create reliable software This text offers a comprehensive and integrated approach to software quality engineering. By following the author's clear guidance, readers learn how to master the techniques to produce high-quality, reliable software, regardless of the software system's level of complexity. The first part of the publication introduces major topics in software quality engineering and presents quality planning as an integral part of the process. Providing readers with a solid foundation in key concepts and practices, the book moves on to offer in-depth coverage of software testing as a primary means to ensure software quality; alternatives for quality assurance, including defect prevention, process improvement, inspection, formal verification, fault tolerance, safety assurance, and damage control; and measurement and analysis to close the feedback loop for quality assessment and quantifiable improvement. The text's approach and style evolved from the author's hands-on experience in the classroom. All the pedagogical tools needed to facilitate quick learning are provided: * Figures and tables that clarify concepts and provide quick topic summaries * Examples that illustrate how theory is applied in real-world situations * Comprehensive bibliography that leads to in-depth discussion of specialized topics * Problem sets at the end of each chapter that test readers' knowledge This is a superior textbook for software engineering, computer science, information systems, and electrical engineering students, and a dependable reference for software and computer professionals and engineers.
Download or read book Mobile Technologies and Applications for the Internet of Things written by Michael E. Auer and published by Springer. This book was released on 2019-04-17 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses and assesses the latest trends in the interactive mobile field, and presents the outcomes of the 12th International Conference on Interactive Mobile Communication Technologies and Learning (IMCL2018), which was held in Hamilton, Canada on October 11 and 12, 2018. Today, interactive mobile technologies are at the core of many – if not all – fields of society. Not only does the younger generation of students expect a mobile working and learning environment, but also the new ideas, technologies and solutions coming out practically every day are further strengthening this trend. Since its inception in 2006, the conference has been devoted to highlighting new approaches in interactive mobile technologies with a focus on learning. The IMCL conferences have since established themselves as a valuable forum for exchanging and discussing new research results and relevant trends, as well as practical experience and best-practice examples. This book contains papers in the fields of: Interactive Collaborative Mobile Learning Environments Mobile Health Care Training Game-based Learning Design of Internet of Things (IoT) Devices and Applications Assessment and Quality in Mobile Learning. Its potential readership includes policymakers, educators and researchers in pedagogy and learning theory, schoolteachers, the learning industry, further education lecturers, etc.
Download or read book Knowledge Management in Organizations written by Lorna Uden and published by Springer. This book was released on 2019-06-11 with total page 549 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book contains the refereed proceedings of the 14th International Conference on Knowledge Management in Organizations, KMO 2019, held in Zamora, Spain, in July 2019. The 46 papers accepted for KMO 2019 were selected from 109 submissions and are organized in topical sections on: knowledge management models and analysis; knowledge transfer and learning; knowledge and service innovation; knowledge creation; knowledge and organization; information systems and information science; data mining and intelligent science; social networks and social aspects of KM; big data and IoT; and new trends in IT.
Download or read book Marketing Engineering written by Gary L. Lilien and published by DecisionPro. This book was released on 2004 with total page 545 pages. Available in PDF, EPUB and Kindle. Book excerpt: Accompanying CD-ROM contains ... "26 software programs, help files and tutorials."--Page 4 of cover.
Download or read book SPSS Statistics for Data Analysis and Visualization written by Keith McCormick and published by John Wiley & Sons. This book was released on 2017-05-01 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dive deeper into SPSS Statistics for more efficient, accurate, and sophisticated data analysis and visualization SPSS Statistics for Data Analysis and Visualization goes beyond the basics of SPSS Statistics to show you advanced techniques that exploit the full capabilities of SPSS. The authors explain when and why to use each technique, and then walk you through the execution with a pragmatic, nuts and bolts example. Coverage includes extensive, in-depth discussion of advanced statistical techniques, data visualization, predictive analytics, and SPSS programming, including automation and integration with other languages like R and Python. You'll learn the best methods to power through an analysis, with more efficient, elegant, and accurate code. IBM SPSS Statistics is complex: true mastery requires a deep understanding of statistical theory, the user interface, and programming. Most users don't encounter all of the methods SPSS offers, leaving many little-known modules undiscovered. This book walks you through tools you may have never noticed, and shows you how they can be used to streamline your workflow and enable you to produce more accurate results. Conduct a more efficient and accurate analysis Display complex relationships and create better visualizations Model complex interactions and master predictive analytics Integrate R and Python with SPSS Statistics for more efficient, more powerful code These "hidden tools" can help you produce charts that simply wouldn't be possible any other way, and the support for other programming languages gives you better options for solving complex problems. If you're ready to take advantage of everything this powerful software package has to offer, SPSS Statistics for Data Analysis and Visualization is the expert-led training you need.
Download or read book Innovating with Concept Mapping written by Alberto Cañas and published by Springer. This book was released on 2016-08-20 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 7th International Conference on Concept Mapping, CMC 2016, held in Tallinn, Estonia, in September 2016. The 25 revised full papers presented were carefully reviewed and selected from 135 submissions. The papers address issues such as facilitation of learning; eliciting, capturing, archiving, and using “expert” knowledge; planning instruction; assessment of “deep” understandings; research planning; collaborative knowledge modeling; creation of “knowledge portfolios”; curriculum design; eLearning, and administrative and strategic planning and monitoring.
Download or read book Developments and Advances in Defense and Security written by Álvaro Rocha and published by Springer. This book was released on 2018-04-05 with total page 415 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book includes a selection of articles from The 2018 Multidisciplinary International Conference of Research Applied to Defense and Security (MICRADS’18), held in Salinas, Peninsula de Santa Elena, Ecuador, from April 18 to 20, 2018. MICRADS is an international forum for researchers and practitioners to present and discuss the most recent innovations, trends, results, experiences and concerns in the various areas of defense and security, together with their technological development and applications. The main topics covered are: Information and Communication Technology in Education; Computer Vision in Military Applications; Engineering Analysis and Signal Processing; Cybersecurity and Cyberdefense; Maritime Security and Safety; Strategy, Geopolitics and Oceanopolitics; Defense planning; Leadership (e-leadership); Defense Economics; Defense Logistics; Health Informatics in Military Applications; Simulation in Military Applications; Computer Networks, Mobility and Pervasive Systems; Military Marketing; Military Physical Training; Assistive Devices and Wearable Technology; Naval and Military Engineering; Weapons and Combat Systems; Operational Oceanography. The book is aimed at all those dealing with defense and security issues, including practitioners, researchers and teachers as well as undergraduate, graduate, master’s and doctorate students.
Download or read book Data Mining written by Ian H. Witten and published by Morgan Kaufmann. This book was released on 2000 with total page 414 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book offers a thorough grounding in machine learning concepts combined with practical advice on applying machine learning tools and techniques in real-world data mining situations. Clearly written and effectively illustrated, this book is ideal for anyone involved at any level in the work of extracting usable knowledge from large collections of data. Complementing the book's instruction is fully functional machine learning software.
Download or read book The Mathematics of the Uncertain written by Eduardo Gil and published by Springer. This book was released on 2018-02-28 with total page 897 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a tribute to Professor Pedro Gil, who created the Department of Statistics, OR and TM at the University of Oviedo, and a former President of the Spanish Society of Statistics and OR (SEIO). In more than eighty original contributions, it illustrates the extent to which Mathematics can help manage uncertainty, a factor that is inherent to real life. Today it goes without saying that, in order to model experiments and systems and to analyze related outcomes and data, it is necessary to consider formal ideas and develop scientific approaches and techniques for dealing with uncertainty. Mathematics is crucial in this endeavor, as this book demonstrates. As Professor Pedro Gil highlighted twenty years ago, there are several well-known mathematical branches for this purpose, including Mathematics of chance (Probability and Statistics), Mathematics of communication (Information Theory), and Mathematics of imprecision (Fuzzy Sets Theory and others). These branches often intertwine, since different sources of uncertainty can coexist, and they are not exhaustive. While most of the papers presented here address the three aforementioned fields, some hail from other Mathematical disciplines such as Operations Research; others, in turn, put the spotlight on real-world studies and applications. The intended audience of this book is mainly statisticians, mathematicians and computer scientists, but practitioners in these areas will certainly also find the book a very interesting read.
Download or read book Artificial Intelligence in Education written by Wayne Holmes and published by . This book was released on 2019-02-28 with total page 244 pages. Available in PDF, EPUB and Kindle. Book excerpt: "The landscape for education has been rapidly changing in the last years: demographic changes affecting the makeup of families, multiple school options available to children, wealth disparities, the global economy demanding new skills from workers, and continued breakthroughs in technology are some of the factors impacting education. Given these changes, how can schools continue to prepare students for the future? In a world where information is readily available online, how can schools continue to be relevant? The emergence of Artificial Intelligence (AI) has exacerbated the need to have these conversations. Its impact on education and the multiple possibilities that it offers are putting pressure on educational leaders to reformulate the school curriculum and the channels to deliver it. The book "Artificial Intelligence in Education, Promises and Implications for Teaching and Learning" by the Center for Curriculum Redesign immerses the reader in a discussion on what to teach students in the era of AI and examines how AI is already demanding much needed updates to the school curriculum, including modernizing its content, focusing on core concepts, and embedding interdisciplinary themes and competencies with the end goal of making learning more enjoyable and useful in students' lives. The second part of the book dives into the history of AI in education, its techniques and applications -including the way AI can help teachers be more effective, and finishes on a reflection about the social aspects of AI. This book is a must-read for educators and policy-makers who want to prepare schools to face the uncertainties of the future and keep them relevant." --Amada Torres, VP, Studies, Insights, and Research, National Association of Independent School (NAIS) "The rapid advances in technology in recent decades have already brought about substantial changes in education, opening up new opportunities to teach and learn anywhere anytime and providing new tools and methods to improve learning outcomes and support innovative teaching and learning.Research into artificial intelligence and machine learning in education goes back to the late 1970s. Artificial intelligence methods were generally employed in two ways: to design and facilitate interactive learning environments that would support learning by doing, and to design and implement tutoring systems by adapting instructions with respect to the students' knowledge state.But this is just the beginning. As Artificial Intelligence in Education shows, AI is increasingly used in education and learning contexts. The collision of three areas - data, computation and education - is set to have far-reaching consequences, raising fundamental questions about the nature of education: what is taught and how it is taught. Artificial Intelligence in Education is an important, if at times disturbing, contribution to the debate on AI and provides a detailed analysis on how it may affect the way teachers and students engage in education. The book describes how artificial intelligence may impact on curriculum design, on the individualisation of learning, and on assessment, offering some tantalising glimpses into the future (the end of exams, your very own lifelong learning companion) while not falling victim to tech-hype. The enormous ethical, technical and pedagogical challenges ahead are spelt out, and there is a real risk that the rapid advances in artificial intelligence products and services will outstrip education systems' capacity to understand, manage and integrate them appropriately. As the book concludes: "We can either leave it to others (the computer scientists, AI engineers and big tech companies) to decide how artificial intelligence in education unfolds, or we can engage in productive dialogue."I commend this book to anyone concerned with the future of education in a digital world." --Marc Durando, Executive Director, European Schoolnet
Download or read book Digital Literacies written by Mark Pegrum and published by Routledge. This book was released on 2014-06-03 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: Dramatic shifts in our communication landscape have made it crucial for language teaching to go beyond print literacy and encompass the digital literacies which are increasingly central to learners' personal, social, educational and professional lives. By situating these digital literacies within a clear theoretical framework, this book provides educators and students alike with not just the background for a deeper understanding of these key 21st-century skills, but also the rationale for integrating these skills into classroom practice. This is the first methodology book to address not just why but also how to teach digital literacies in the English language classroom. This book provides: A theoretical framework through which to categorise and prioritise digital literacies Practical classroom activities to help learners and teachers develop digital literacies in tandem with key language skills A thorough analysis of the pedagogical implications of developing digital literacies in teaching practice A consideration of exactly how to integrate digital literacies into the English language syllabus Suggestions for teachers on how to continue their own professional development through PLNs (Personal Learning Networks), and how to access teacher development opportunities online This book is ideal for English language teachers and learners of all age groups and levels, academics and students researching digital literacies, and anyone looking to expand their understanding of digital literacies within a teaching framework.