[PDF] Learning Management Back From Machines eBook

Author : Muthukrishnan Kalyanasundaram
Publisher : Partridge Publishing
Page : 234 pages
File Size : 41,64 MB
Release : 2020-12-27
Category : Education
ISBN : 1482844907

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Technology driven witty solutions to everyday Managerial Problems Like it is often told “Solutions at your doorstep”, we are completely surrounded by profound managerial solutions waiting to be unearthed from our everyday machines in the form of phones, computers, safety devices, automobile etc. The world of machines abounds with managerial thoughts and solutions. This inspiring book provides us with a new approach in problem solving and addresses the diverse challenges faced in managerial functions today. “Learning Management Back From Machines”, is the wonderful story of Krish and his latest creation, MANU – an advanced hyper-intelligent, direct-neural interface-capable humanoid, which helps Krish along in deriving managerial solutions from fellow-machines and machine-processes alike. In the process of learning and observing the history of various technological marvels along with the need for these inventions, we discover a whole new dimension of creative intelligence and learning, waiting to reveal itself all over again. The book is aimed at understanding the core essence of how machines have been made to work and help us discover new and innovative solutions to our everyday social and managerial problems. • RELIGIONS TEACH US MANAGEMENT. • STORIES AND FABLES TEACH US MANAGEMENT. • MANAGEMENT THEORIES TEACH US MANAGEMENT. • NOW EVERYDAY MACHINES WILL TEACH US MANAGEMENT

Author : Audrey Watters
Publisher : MIT Press
Page : 325 pages
File Size : 23,38 MB
Release : 2023-02-07
Category : Education
ISBN : 026254606X

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How ed tech was born: Twentieth-century teaching machines--from Sidney Pressey's mechanized test-giver to B. F. Skinner's behaviorist bell-ringing box. Contrary to popular belief, ed tech did not begin with videos on the internet. The idea of technology that would allow students to "go at their own pace" did not originate in Silicon Valley. In Teaching Machines, education writer Audrey Watters offers a lively history of predigital educational technology, from Sidney Pressey's mechanized positive-reinforcement provider to B. F. Skinner's behaviorist bell-ringing box. Watters shows that these machines and the pedagogy that accompanied them sprang from ideas--bite-sized content, individualized instruction--that had legs and were later picked up by textbook publishers and early advocates for computerized learning. Watters pays particular attention to the role of the media--newspapers, magazines, television, and film--in shaping people's perceptions of teaching machines as well as the psychological theories underpinning them. She considers these machines in the context of education reform, the political reverberations of Sputnik, and the rise of the testing and textbook industries. She chronicles Skinner's attempts to bring his teaching machines to market, culminating in the famous behaviorist's efforts to launch Didak 101, the "pre-verbal" machine that taught spelling. (Alternate names proposed by Skinner include "Autodidak," "Instructomat," and "Autostructor.") Telling these somewhat cautionary tales, Watters challenges what she calls "the teleology of ed tech"--the idea that not only is computerized education inevitable, but technological progress is the sole driver of events.

Author : Ian H. Witten
Publisher : Elsevier
Page : 665 pages
File Size : 12,16 MB
Release : 2011-02-03
Category : Computers
ISBN : 0080890369

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Data Mining: Practical Machine Learning Tools and Techniques, Third Edition, offers a thorough grounding in machine learning concepts as well as practical advice on applying machine learning tools and techniques in real-world data mining situations. This highly anticipated third edition of the most acclaimed work on data mining and machine learning will teach you everything you need to know about preparing inputs, interpreting outputs, evaluating results, and the algorithmic methods at the heart of successful data mining. Thorough updates reflect the technical changes and modernizations that have taken place in the field since the last edition, including new material on Data Transformations, Ensemble Learning, Massive Data Sets, Multi-instance Learning, plus a new version of the popular Weka machine learning software developed by the authors. Witten, Frank, and Hall include both tried-and-true techniques of today as well as methods at the leading edge of contemporary research. The book is targeted at information systems practitioners, programmers, consultants, developers, information technology managers, specification writers, data analysts, data modelers, database R&D professionals, data warehouse engineers, data mining professionals. The book will also be useful for professors and students of upper-level undergraduate and graduate-level data mining and machine learning courses who want to incorporate data mining as part of their data management knowledge base and expertise. Provides a thorough grounding in machine learning concepts as well as practical advice on applying the tools and techniques to your data mining projects Offers concrete tips and techniques for performance improvement that work by transforming the input or output in machine learning methods Includes downloadable Weka software toolkit, a collection of machine learning algorithms for data mining tasks—in an updated, interactive interface. Algorithms in toolkit cover: data pre-processing, classification, regression, clustering, association rules, visualization

Author : Sofia B. Dias
Publisher : Springer Science & Business Media
Page : 243 pages
File Size : 32,35 MB
Release : 2013-09-29
Category : Technology & Engineering
ISBN : 3319020781

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What are the key channels to change in blended instructional practice as they relate to the use of a learning management system (LMS)? What role LMS users’ profiles play in facilitating change in practice? Can we model users’ quality of interaction (QoI) with LMS? How inclusiveness and affectiveness could lead to a personalized intelligent LMS (iLMS)? If these questions sound intrinsic to you and to your own experience and circumstance, then this book fits absolutely to you. Here, the term Blended – viewed as a fuzzy concept – is understood as a stepping-stone on the way to the future, to explain the multiple ways human beings think/act/feel of society in the 21st century and to embrace the opportunity of humans to re/co-construct new knowledge through the intermediation role of the technology. Initially, based on an online learning environment’ theoretical framework, some current issues of the educational processes in the digital age of Web 2.0 are analyzed. Then, after exploring the main methodological procedures, characteristic examples of research case studies follow, including LMS users’ trends and profiles and modeling of their QoI using fuzzy logic. This book offers useful information that evokes initiatives towards rethinking of the value, efficiency, inclusiveness, affectiveness and personalization of the iLMS-based b-learning environment, both by the educators, the LMS designers and educational policy decision makers.

Author : Kats, Yefim
Publisher : IGI Global
Page : 486 pages
File Size : 48,34 MB
Release : 2010-05-31
Category : Technology & Engineering
ISBN : 1615208542

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"This book gives a general coverage of learning management systems followed by a comparative analysis of the particular LMS products, review of technologies supporting different aspect of educational process, and, the best practices and methodologies for LMS-supported course delivery"--Provided by publisher.

Author : Jitendra Kumar
Publisher : CRC Press
Page : 199 pages
File Size : 18,82 MB
Release : 2021-11-25
Category : Computers
ISBN : 1000476596

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Cloud computing offers subscription-based on-demand services, and it has emerged as the backbone of the computing industry. It has enabled us to share resources among multiple users through virtualization, which creates a virtual instance of a computer system running in an abstracted hardware layer. Unlike early distributed computing models, it offers virtually limitless computing resources through its large scale cloud data centers. It has gained wide popularity over the past few years, with an ever-increasing infrastructure, a number of users, and the amount of hosted data. The large and complex workloads hosted on these data centers introduce many challenges, including resource utilization, power consumption, scalability, and operational cost. Therefore, an effective resource management scheme is essential to achieve operational efficiency with improved elasticity. Machine learning enabled solutions are the best fit to address these issues as they can analyze and learn from the data. Moreover, it brings automation to the solutions, which is an essential factor in dealing with large distributed systems in the cloud paradigm. Machine Learning for Cloud Management explores cloud resource management through predictive modelling and virtual machine placement. The predictive approaches are developed using regression-based time series analysis and neural network models. The neural network-based models are primarily trained using evolutionary algorithms, and efficient virtual machine placement schemes are developed using multi-objective genetic algorithms. Key Features: The first book to set out a range of machine learning methods for efficient resource management in a large distributed network of clouds. Predictive analytics is an integral part of efficient cloud resource management, and this book gives a future research direction to researchers in this domain. It is written by leading international researchers. The book is ideal for researchers who are working in the domain of cloud computing.

Author : Emmanuel Jurczenko
Publisher : John Wiley & Sons
Page : 460 pages
File Size : 21,96 MB
Release : 2020-10-06
Category : Business & Economics
ISBN : 1786305445

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This new edited volume consists of a collection of original articles written by leading financial economists and industry experts in the area of machine learning for asset management. The chapters introduce the reader to some of the latest research developments in the area of equity, multi-asset and factor investing. Each chapter deals with new methods for return and risk forecasting, stock selection, portfolio construction, performance attribution and transaction costs modeling. This volume will be of great help to portfolio managers, asset owners and consultants, as well as academics and students who want to improve their knowledge of machine learning in asset management.

Author : Ashok N. Srivastava
Publisher : CRC Press
Page : 489 pages
File Size : 12,58 MB
Release : 2016-04-19
Category : Computers
ISBN : 1439841799

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This volume presents state-of-the-art tools and techniques for automatically detecting, diagnosing, and predicting the effects of adverse events in an engineered system. It emphasizes the importance of these techniques in managing the intricate interactions within and between engineering systems to maintain a high degree of reliability. Reflecting the interdisciplinary nature of the field, the book explains how the fundamental algorithms and methods of both physics-based and data-driven approaches effectively address systems health management in application areas such as data centers, aircraft, and software systems.

Author : Wang, Victor C. X.
Publisher : IGI Global
Page : 1471 pages
File Size : 30,99 MB
Release : 2014-05-31
Category : Education
ISBN : 1466660473

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Technology has become an integral part of our everyday lives. This trend in ubiquitous technology has also found its way into the learning process at every level of education. The Handbook of Research on Education and Technology in a Changing Society offers an in-depth description of concepts related to different areas, issues, and trends within education and technological integration in modern society. This handbook includes definitions and terms, as well as explanations of concepts and processes regarding the integration of technology into education. Addressing all pertinent issues and concerns in education and technology in our changing society with a wide breadth of discussion, this handbook is an essential collection for educators, academicians, students, researchers, and librarians.

Author : Gulzar, Zameer
Publisher : IGI Global
Page : 336 pages
File Size : 16,53 MB
Release : 2021-05-14
Category : Education
ISBN : 1799850102

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Technology is currently playing a vital role in revolutionizing education systems and progressing academia into the digital age. Technological methods including data mining and machine learning are assisting with the discovery of new techniques for improving learning environments in regions across the world. As the educational landscape continues to rapidly transform, researchers and administrators need to stay up to date on the latest advancements in order to elevate the quality of teaching in their specific institutions. Machine Learning Approaches for Improvising Modern Learning Systems provides emerging research exploring the theoretical and practical aspects of technological enhancements in educational environments and the popularization of contemporary learning methods in developing countries. Featuring coverage on a broad range of topics such as game-based learning, intelligent tutoring systems, and course modelling, this book is ideally designed for researchers, scholars, administrators, policymakers, students, practitioners, and educators seeking current research on the digital transformation of educational institutions.