Learning In Real Time

Author : Yoon, Jiyoon,Semingson, Peggy
Publisher : IGI Global
Page : 356 pages
File Size : 48,5 Mb
Release : 2019-04-19
Category : Education
ISBN : 9781522575689

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Educational Technology and Resources for Synchronous Learning in Higher Education by Yoon, Jiyoon,Semingson, Peggy Pdf

As more classes move to online instruction, there is a need for research that shows the effectiveness of synchronous learning. Educators must guide students on how to use these new learning tools and become aware of the research trends and opportunities within these developing online and hybrid courses. Educational Technology and Resources for Synchronous Learning in Higher Education provides evidence-based practice on incorporating synchronous teaching tools and practice within online courses to enhance content mastery and community development. Additionally, the book presents a strong theoretical overview of the topic and allows readers to develop a more nuanced understanding of the benefits and constraints of synchronous learning. Covering topics such as game learning, online communication, and professional development, it is designed for online instructors, instructional designers, administrators, students, and researchers and educators in higher education, as well as corporate, military, and government sectors.

Author : Mahrishi, Mehul,Hiran, Kamal Kant,Meena, Gaurav,Sharma, Paawan
Publisher : IGI Global
Page : 344 pages
File Size : 51,8 Mb
Release : 2020-04-24
Category : Computers
ISBN : 9781799830979

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Machine Learning and Deep Learning in Real-Time Applications by Mahrishi, Mehul,Hiran, Kamal Kant,Meena, Gaurav,Sharma, Paawan Pdf

Artificial intelligence and its various components are rapidly engulfing almost every professional industry. Specific features of AI that have proven to be vital solutions to numerous real-world issues are machine learning and deep learning. These intelligent agents unlock higher levels of performance and efficiency, creating a wide span of industrial applications. However, there is a lack of research on the specific uses of machine/deep learning in the professional realm. Machine Learning and Deep Learning in Real-Time Applications provides emerging research exploring the theoretical and practical aspects of machine learning and deep learning and their implementations as well as their ability to solve real-world problems within several professional disciplines including healthcare, business, and computer science. Featuring coverage on a broad range of topics such as image processing, medical improvements, and smart grids, this book is ideally designed for researchers, academicians, scientists, industry experts, scholars, IT professionals, engineers, and students seeking current research on the multifaceted uses and implementations of machine learning and deep learning across the globe.

Author : Jian-Xin Xu,Sanjib K. Panda,Tong Heng Lee
Publisher : Springer Science & Business Media
Page : 204 pages
File Size : 54,8 Mb
Release : 2008-12-12
Category : Technology & Engineering
ISBN : 9781848821750

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Real-time Iterative Learning Control by Jian-Xin Xu,Sanjib K. Panda,Tong Heng Lee Pdf

Real-time Iterative Learning Control demonstrates how the latest advances in iterative learning control (ILC) can be applied to a number of plants widely encountered in practice. The book gives a systematic introduction to real-time ILC design and source of illustrative case studies for ILC problem solving; the fundamental concepts, schematics, configurations and generic guidelines for ILC design and implementation are enhanced by a well-selected group of representative, simple and easy-to-learn example applications. Key issues in ILC design and implementation in linear and nonlinear plants pervading mechatronics and batch processes are addressed, in particular: ILC design in the continuous- and discrete-time domains; design in the frequency and time domains; design with problem-specific performance objectives including robustness and optimality; design in a modular approach by integration with other control techniques; and design by means of classical tools based on Bode plots and state space.

Author : Jonathan E. Finkelstein
Publisher : John Wiley & Sons
Page : 5 pages
File Size : 45,7 Mb
Release : 2009-10-06
Category : Education
ISBN : 9780470596623

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Learning in Real Time by Jonathan E. Finkelstein Pdf

Learning in Real Time is a concise and practical resource for education professionals teaching live and online or those wanting to humanize and improve interaction in their online courses by adding a synchronous learning component. The book offers keen insight into the world of synchronous learning tools, guides instructors in evaluating how and when to use them, and illustrates how educators can develop their own strategies and styles in implementing such tools to improve online learning.

Author : Carla Meskill
Publisher : Athelstan
Page : 216 pages
File Size : 51,6 Mb
Release : 2002
Category : Language acquisition
ISBN : 9780940753174

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Teaching and Learning in Real Time by Carla Meskill Pdf

This title explores technology use for second language learners, focussing on sociocognitive development, media awareness, second language acquisition strategies and interpersonal interactions. Topics include: instructional media and teachnology and language learning; The Media as a Second Language; principled uses of media and technologies; the aural -- talking about, around and through audio technologies; video -- the What, the Why, the How; computers in language learning -- from Constructed to Constructing; computer communication tools; multimedia spaces, performances, and characters; electronic literacy as a Second Language.

Author : Negash, Solomon,Whitman, Michael,Woszczynski, Amy,Hoganson, Ken,Mattord, Herbert
Publisher : IGI Global
Page : 406 pages
File Size : 49,8 Mb
Release : 2008-05-31
Category : Computers
ISBN : 9781599049656

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Handbook of Distance Learning for Real-Time and Asynchronous Information Technology Education by Negash, Solomon,Whitman, Michael,Woszczynski, Amy,Hoganson, Ken,Mattord, Herbert Pdf

"This book looks at solutions that provide the best fits of distance learning technologies for the teacher and learner presented by sharing teacher experiences in information technology education"--Provided by publisher.

Author : Albert Bifet,Ricard Gavalda,Geoffrey Holmes,Bernhard Pfahringer
Publisher : MIT Press
Page : 289 pages
File Size : 51,8 Mb
Release : 2023-05-09
Category : Computers
ISBN : 9780262547833

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Machine Learning for Data Streams by Albert Bifet,Ricard Gavalda,Geoffrey Holmes,Bernhard Pfahringer Pdf

A hands-on approach to tasks and techniques in data stream mining and real-time analytics, with examples in MOA, a popular freely available open-source software framework. Today many information sources—including sensor networks, financial markets, social networks, and healthcare monitoring—are so-called data streams, arriving sequentially and at high speed. Analysis must take place in real time, with partial data and without the capacity to store the entire data set. This book presents algorithms and techniques used in data stream mining and real-time analytics. Taking a hands-on approach, the book demonstrates the techniques using MOA (Massive Online Analysis), a popular, freely available open-source software framework, allowing readers to try out the techniques after reading the explanations. The book first offers a brief introduction to the topic, covering big data mining, basic methodologies for mining data streams, and a simple example of MOA. More detailed discussions follow, with chapters on sketching techniques, change, classification, ensemble methods, regression, clustering, and frequent pattern mining. Most of these chapters include exercises, an MOA-based lab session, or both. Finally, the book discusses the MOA software, covering the MOA graphical user interface, the command line, use of its API, and the development of new methods within MOA. The book will be an essential reference for readers who want to use data stream mining as a tool, researchers in innovation or data stream mining, and programmers who want to create new algorithms for MOA.

Author : Piotr Antonik
Publisher : Springer
Page : 171 pages
File Size : 40,9 Mb
Release : 2018-05-18
Category : Science
ISBN : 9783319910536

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Application of FPGA to Real‐Time Machine Learning by Piotr Antonik Pdf

This book lies at the interface of machine learning – a subfield of computer science that develops algorithms for challenging tasks such as shape or image recognition, where traditional algorithms fail – and photonics – the physical science of light, which underlies many of the optical communications technologies used in our information society. It provides a thorough introduction to reservoir computing and field-programmable gate arrays (FPGAs). Recently, photonic implementations of reservoir computing (a machine learning algorithm based on artificial neural networks) have made a breakthrough in optical computing possible. In this book, the author pushes the performance of these systems significantly beyond what was achieved before. By interfacing a photonic reservoir computer with a high-speed electronic device (an FPGA), the author successfully interacts with the reservoir computer in real time, allowing him to considerably expand its capabilities and range of possible applications. Furthermore, the author draws on his expertise in machine learning and FPGA programming to make progress on a very different problem, namely the real-time image analysis of optical coherence tomography for atherosclerotic arteries.

Author : Jeremy Howard,Sylvain Gugger
Publisher : O'Reilly Media
Page : 624 pages
File Size : 40,9 Mb
Release : 2020-06-29
Category : Computers
ISBN : 9781492045496

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Deep Learning for Coders with fastai and PyTorch by Jeremy Howard,Sylvain Gugger Pdf

Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala

Author : Smriti Srivastava,Manju Khari,Ruben Gonzalez Crespo,Gopal Chaudhary,Parul Arora
Publisher : Springer Nature
Page : 212 pages
File Size : 40,6 Mb
Release : 2021-09-23
Category : Technology & Engineering
ISBN : 9783030761677

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Concepts and Real-Time Applications of Deep Learning by Smriti Srivastava,Manju Khari,Ruben Gonzalez Crespo,Gopal Chaudhary,Parul Arora Pdf

This book provides readers with a comprehensive and recent exposition in deep learning and its multidisciplinary applications, with a concentration on advances of deep learning architectures. The book discusses various artificial intelligence (AI) techniques based on deep learning architecture with applications in natural language processing, semantic knowledge, forecasting and many more. The authors shed light on various applications that can benefit from the use of deep learning in pattern recognition, person re-identification in surveillance videos, action recognition in videos, image and video captioning. The book also highlights how deep learning concepts can be interwoven with more modern concepts to yield applications in multidisciplinary fields. Presents a comprehensive look at deep learning and its multidisciplinary applications, concentrating on advances of deep learning architectures; Includes a survey of deep learning problems and solutions, identifying the main open issues, innovations and latest technologies; Shows industrial deep learning in practice with examples/cases, efforts, challenges, and strategic approaches.

Author : Toru Ishida
Publisher : Springer
Page : 137 pages
File Size : 41,6 Mb
Release : 2007-08-28
Category : Computers
ISBN : 9780585345079

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Real-Time Search for Learning Autonomous Agents by Toru Ishida Pdf

Autonomous agents or multiagent systems are computational systems in which several computational agents interact or work together to perform some set of tasks. These systems may involve computational agents having common goals or distinct goals. Real-Time Search for Learning Autonomous Agents focuses on extending real-time search algorithms for autonomous agents and for a multiagent world. Although real-time search provides an attractive framework for resource-bounded problem solving, the behavior of the problem solver is not rational enough for autonomous agents. The problem solver always keeps the record of its moves and the problem solver cannot utilize and improve previous experiments. Other problems are that although the algorithms interleave planning and execution, they cannot be directly applied to a multiagent world. The problem solver cannot adapt to the dynamically changing goals and the problem solver cannot cooperatively solve problems with other problem solvers. This book deals with all these issues. Real-Time Search for Learning Autonomous Agents serves as an excellent resource for researchers and engineers interested in both practical references and some theoretical basis for agent/multiagent systems. The book can also be used as a text for advanced courses on the subject.

Author : Peggy L. Maki
Publisher : Taylor & Francis
Page : 198 pages
File Size : 49,9 Mb
Release : 2023-07-03
Category : Education
ISBN : 9781000977912

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Real-Time Student Assessment by Peggy L. Maki Pdf

This book challenges institutions and their programs to prioritize the use of chronological assessment results to benefit enrolled students in comparison with the more common practice of prolonged assessment cycles that generally benefit future students. Peggy Maki advocates for real-time assessment processes to identify patterns of underperformance and obstacles that require timely interventions for enrolled students to succeed. In tandem with the sets of educational practices and policies that many institutions have now undertaken to close achievement and graduation rates across our diverse student demographics, such as developing clear degree pathways, she calls on all higher education providers – if they are to remain relevant and meet their social purpose in our complex world – to urgently recalibrate their assessment processes to focus on currently enrolled students’ progress towards achieving a high-quality degree, regardless of when they matriculate or re-enter higher education. She demonstrates that we already have sufficient examples and evidence to implement real-time assessment of students as they progress through their studies. She draws on the practices of specialized accredited programs, such as those in the professions that assess in real time; on the experiences of institutions that have adopted competency-based education; and on the affordances of technologies that now provide faculty and students with up-to-the-minute diagnostics. She identifies the six principles necessary to implement a real-time assessment process, illustrated by case studies of how campuses have operationalized them to advance students’ equitable progress towards achieving a high-quality degree; and demonstrates the benefits of real-time assessment compared to more future-oriented processes, among which is engaging students in reflecting on their own progress along their degree pathways.She advocates for the use of well documented national outcomes-based frameworks such as Liberal Education and America’s Promise (LEAP), its aligned Valid Assessment of Learning in Undergraduate Education scoring rubrics ( VALUE), the Degree Qualifications Profile, and discipline-based outcomes assessments to ensure high-quality degrees that meet well-defined standards and criteria. She also identifies how data systems and technological developments help to monitor closely and respond in time to students’ patterns of underperformance.The book is an urgent call for higher education to achieve the values of equity, transparency and quality it espouses; and ensure that all students graduate in a timely fashion with the competencies they need to be active and productive citizens.

Author : Mandakini Chagamreddy
Publisher : Archers & Elevators Publishing House
Page : 72 pages
File Size : 54,8 Mb
Release : 2024-06-29
Category : Antiques & Collectibles
ISBN : 9788119385409

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Deep Learning and Natural Language Processing Based Real-Time Applications by Mandakini Chagamreddy Pdf

Author : Tom J. van Weert,Arthur Tatnall
Publisher : Springer
Page : 288 pages
File Size : 49,8 Mb
Release : 2006-01-28
Category : Education
ISBN : 9780387259970

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Information and Communication Technologies and Real-Life Learning by Tom J. van Weert,Arthur Tatnall Pdf

Information and Communication Technologies in Real-Life Learning presents the results of an International Federation for Information Processing (IFIP) working conference held December 2004 in Melbourne, Australia. The working conference was organized by IFIP Working Group 3.2 (Informatics and ICT in Higher Education) and IFIP Working Group 3.4 (Professional and Vocational Education in Information Technology). The papers in this book present a cross-section of issues in real-life learning in which Information and Communication Technology (ICT) plays an important role. Some of the issues covered include: education models for real-life learning enabled by ICT; effective organization of a real-life learning environment; the changing role of the student; the changing role of educational institutions and their relationship with business and industry; the changing role of teachers and their use of ICT; and managment of ICT-rich education change.

Author : Henrik Brink,Joseph Richards,Mark Fetherolf
Publisher : Simon and Schuster
Page : 380 pages
File Size : 44,9 Mb
Release : 2016-09-15
Category : Computers
ISBN : 9781638357001

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Real-World Machine Learning by Henrik Brink,Joseph Richards,Mark Fetherolf Pdf

Summary Real-World Machine Learning is a practical guide designed to teach working developers the art of ML project execution. Without overdosing you on academic theory and complex mathematics, it introduces the day-to-day practice of machine learning, preparing you to successfully build and deploy powerful ML systems. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications. About the Technology Machine learning systems help you find valuable insights and patterns in data, which you'd never recognize with traditional methods. In the real world, ML techniques give you a way to identify trends, forecast behavior, and make fact-based recommendations. It's a hot and growing field, and up-to-speed ML developers are in demand. About the Book Real-World Machine Learning will teach you the concepts and techniques you need to be a successful machine learning practitioner without overdosing you on abstract theory and complex mathematics. By working through immediately relevant examples in Python, you'll build skills in data acquisition and modeling, classification, and regression. You'll also explore the most important tasks like model validation, optimization, scalability, and real-time streaming. When you're done, you'll be ready to successfully build, deploy, and maintain your own powerful ML systems. What's Inside Predicting future behavior Performance evaluation and optimization Analyzing sentiment and making recommendations About the Reader No prior machine learning experience assumed. Readers should know Python. About the Authors Henrik Brink, Joseph Richards and Mark Fetherolf are experienced data scientists engaged in the daily practice of machine learning. Table of Contents PART 1: THE MACHINE-LEARNING WORKFLOW What is machine learning? Real-world data Modeling and prediction Model evaluation and optimization Basic feature engineering PART 2: PRACTICAL APPLICATION Example: NYC taxi data Advanced feature engineering Advanced NLP example: movie review sentiment Scaling machine-learning workflows Example: digital display advertising