Download or read book Learning Management Back from Machines written by Muthukrishnan Kalyanasundaram and published by Partridge Publishing. This book was released on 2020-12-27 with total page 234 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Teaching Machines written by Audrey Watters and published by MIT Press. This book was released on 2023-02-07 with total page 325 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Data Mining written by Ian H. Witten and published by Elsevier. This book was released on 2011-02-03 with total page 665 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Download or read book Towards an Intelligent Learning Management System Under Blended Learning written by Sofia B. Dias and published by Springer Science & Business Media. This book was released on 2013-09-29 with total page 243 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Teaching Machines written by Bill Ferster and published by JHU Press. This book was released on 2014-11-17 with total page 216 pages. Available in PDF, EPUB and Kindle. Book excerpt: Technology promises to make learning better, cheaper, faster—but rarely has it kept that promise. The allure of educational technology is easy to understand. Classroom instruction is an expensive and time-consuming process fraught with contradictory theories and frustratingly uneven results. Educators, inspired by machines’ contributions to modern life, have been using technology to facilitate teaching for centuries. In Teaching Machines, Bill Ferster examines past attempts to automate instruction from the earliest use of the postal service for distance education to the current maelstrom surrounding Massive Open Online Courses. He tells the stories of the entrepreneurs and visionaries who, beginning in the colonial era, developed and promoted various instructional technologies. Ferster touches on a wide range of attempts to enhance the classroom experience with machines, from hornbooks, the Chautauqua movement, and correspondence courses to B. F. Skinner’s teaching machine, intelligent tutoring systems, and eLearning. The famed progressive teachers, researchers, and administrators that the book highlights often overcame substantial hurdles to implement their ideas, but not all of them succeeded in improving the quality of education. Teaching Machines provides invaluable new insight into our current debate over the efficacy of educational technology.

Download or read book Education Is Not an App written by Jonathan A. Poritz and published by Routledge. This book was released on 2016-08-12 with total page 224 pages. Available in PDF, EPUB and Kindle. Book excerpt: Whilst much has been written about the doors that technology can open for students, less has been said about its impact on teachers and professors. Although technology undoubtedly brings with it huge opportunities within higher education, there is also the fear that it will have a negative effect both on faculty and on teaching standards. Education Is Not an App offers a bold and provocative analysis of the economic context within which educational technology is being implemented, not least the financial problems currently facing higher education institutions around the world. The book emphasizes the issue of control as being a key factor in whether educational technology is used for good purposes or bad purposes, arguing that technology has great potential if placed in caring hands. Whilst it is a guide to the newest developments in education technology, it is also a book for those faculty, technology professionals, and higher education policy-makers who want to understand the economic and pedagogical impact of technology on professors and students. It advocates a path into the future based on faculty autonomy, shared governance, and concentration on the university’s traditional role of promoting the common good. Offering the first critical, in-depth assessment of the political economy of education technology, this book will serve as an invaluable guide to concerned faculty, as well as to anyone with an interest in the future of higher education.

Download or read book Handbook of Research on Education and Technology in a Changing Society written by Wang, Victor C. X. and published by IGI Global. This book was released on 2014-05-31 with total page 1471 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Learning Management System Technologies and Software Solutions for Online Teaching Tools and Applications written by Kats, Yefim and published by IGI Global. This book was released on 2010-05-31 with total page 486 pages. Available in PDF, EPUB and Kindle. Book excerpt: "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.

Download or read book Machine Learning for Cloud Management written by Jitendra Kumar and published by CRC Press. This book was released on 2021-11-25 with total page 199 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Machine Learning Approaches for Improvising Modern Learning Systems written by Gulzar, Zameer and published by IGI Global. This book was released on 2021-05-14 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Learning Management Systems Complete Self Assessment Guide written by Gerardus Blokdyk and published by Createspace Independent Publishing Platform. This book was released on 2017-05-27 with total page 116 pages. Available in PDF, EPUB and Kindle. Book excerpt: Think about the kind of project structure that would be appropriate for your Learning Management Systems project. should it be formal and complex, are can it be less formal and relatively simple? What knowledge, skills and characteristics mark a good Learning Management Systems project manager? What are specific Learning Management Systems Rules to follow? How does the Learning Management Systems manager ensure against scope creep? What are your results for key measures or indicators of the accomplishment of your Learning Management Systems strategy and action plans, including building and strengthening core competencies? Defining, designing, creating, and implementing a process to solve a business challenge or meet a business objective is the most valuable role... In EVERY company, organization and department. Unless you are talking a one-time, single-use project within a business, there should be a process. Whether that process is managed and implemented by humans, AI, or a combination of the two, it needs to be designed by someone with a complex enough perspective to ask the right questions. Someone capable of asking the right questions and step back and say, 'What are we really trying to accomplish here? And is there a different way to look at it?' For more than twenty years, The Art of Service's Self-Assessments empower people who can do just that - whether their title is marketer, entrepreneur, manager, salesperson, consultant, business process manager, executive assistant, IT Manager, CxO etc... - they are the people who rule the future. They are people who watch the process as it happens, and ask the right questions to make the process work better. This book is for managers, advisors, consultants, specialists, professionals and anyone interested in Learning Management Systems assessment. Featuring 609 new and updated case-based questions, organized into seven core areas of process design, this Self-Assessment will help you identify areas in which Learning Management Systems improvements can be made. In using the questions you will be better able to: - diagnose Learning Management Systems projects, initiatives, organizations, businesses and processes using accepted diagnostic standards and practices - implement evidence-based best practice strategies aligned with overall goals - integrate recent advances in Learning Management Systems and process design strategies into practice according to best practice guidelines Using a Self-Assessment tool known as the Learning Management Systems Scorecard, you will develop a clear picture of which Learning Management Systems areas need attention. Included with your purchase of the book is the Learning Management Systems Self-Assessment downloadable resource, containing all 609 questions and Self-Assessment areas of this book. This helps with ease of (re-)use and enables you to import the questions in your preferred Management or Survey Tool. Access instructions can be found in the book. You are free to use the Self-Assessment contents in your presentations and materials for customers without asking us - we are here to help. This Self-Assessment has been approved by The Art of Service as part of a lifelong learning and Self-Assessment program and as a component of maintenance of certification. Optional other Self-Assessments are available. For more information, visit http://theartofservice.com

Download or read book Machine Learning for Asset Management written by Emmanuel Jurczenko and published by John Wiley & Sons. This book was released on 2020-10-06 with total page 460 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Download or read book Machine Learning in Educational Sciences written by Myint Swe Khine and published by Springer Nature. This book was released on with total page 389 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Machine Learning Algorithms for Signal and Image Processing written by Deepika Ghai and published by John Wiley & Sons. This book was released on 2022-11-18 with total page 516 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning Algorithms for Signal and Image Processing Enables readers to understand the fundamental concepts of machine and deep learning techniques with interactive, real-life applications within signal and image processing Machine Learning Algorithms for Signal and Image Processing aids the reader in designing and developing real-world applications using advances in machine learning to aid and enhance speech signal processing, image processing, computer vision, biomedical signal processing, adaptive filtering, and text processing. It includes signal processing techniques applied for pre-processing, feature extraction, source separation, or data decompositions to achieve machine learning tasks. Written by well-qualified authors and contributed to by a team of experts within the field, the work covers a wide range of important topics, such as: Speech recognition, image reconstruction, object classification and detection, and text processing Healthcare monitoring, biomedical systems, and green energy How various machine and deep learning techniques can improve accuracy, precision rate recall rate, and processing time Real applications and examples, including smart sign language recognition, fake news detection in social media, structural damage prediction, and epileptic seizure detection Professionals within the field of signal and image processing seeking to adapt their work further will find immense value in this easy-to-understand yet extremely comprehensive reference work. It is also a worthy resource for students and researchers in related fields who are looking to thoroughly understand the historical and recent developments that have been made in the field.

Download or read book Handbook of Research on Education Institutions Skills and Jobs in the Digital Era written by Ordóñez de Pablos, Patricia and published by IGI Global. This book was released on 2022-09-30 with total page 532 pages. Available in PDF, EPUB and Kindle. Book excerpt: The evolution of information technologies, mobile devices, social media, and the needs of students, workers, and academics has experienced rapid changes in the past several years. This complex and dynamic reality requires new forms of education delivery and teaching methodologies for academics. Old teaching practices must be refreshed to provide customized and context-adapted learning opportunities. Additionally, there are drivers, barriers, and success factors within distance and mobile learning devices and systems that need to be explored and tested. The Handbook of Research on Education Institutions, Skills, and Jobs in the Digital Era aims to foster an international dialogue of approaches, methodologies, and tools for the transformation of education in the digital era and broaden the visibility of new technologies for education, establish an international scientific platform for collaboration on digital education, and accelerate innovation in education technology. Covering critical topics such as faculty training, online teaching, and talent management, this major reference work is ideal for government officials, industry professionals, policymakers, researchers, scholars, academicians, practitioners, instructors, and students.

Download or read book Machine Learning Solutions written by Jalaj Thanaki and published by Packt Publishing Ltd. This book was released on 2018-04-27 with total page 567 pages. Available in PDF, EPUB and Kindle. Book excerpt: Practical, hands-on solutions in Python to overcome any problem in Machine Learning Key Features Master the advanced concepts, methodologies, and use cases of machine learning Build ML applications for analytics, NLP and computer vision domains Solve the most common problems in building machine learning models Book Description Machine learning (ML) helps you find hidden insights from your data without the need for explicit programming. This book is your key to solving any kind of ML problem you might come across in your job. You’ll encounter a set of simple to complex problems while building ML models, and you'll not only resolve these problems, but you’ll also learn how to build projects based on each problem, with a practical approach and easy-to-follow examples. The book includes a wide range of applications: from analytics and NLP, to computer vision domains. Some of the applications you will be working on include stock price prediction, a recommendation engine, building a chat-bot, a facial expression recognition system, and many more. The problem examples we cover include identifying the right algorithm for your dataset and use cases, creating and labeling datasets, getting enough clean data to carry out processing, identifying outliers, overftting datasets, hyperparameter tuning, and more. Here, you'll also learn to make more timely and accurate predictions. In addition, you'll deal with more advanced use cases, such as building a gaming bot, building an extractive summarization tool for medical documents, and you'll also tackle the problems faced while building an ML model. By the end of this book, you'll be able to fine-tune your models as per your needs to deliver maximum productivity. What you will learn Select the right algorithm to derive the best solution in ML domains Perform predictive analysis effciently using ML algorithms Predict stock prices using the stock index value Perform customer analytics for an e-commerce platform Build recommendation engines for various domains Build NLP applications for the health domain Build language generation applications using different NLP techniques Build computer vision applications such as facial emotion recognition Who this book is for This book is for the intermediate users such as machine learning engineers, data engineers, data scientists, and more, who want to solve simple to complex machine learning problems in their day-to-day work and build powerful and efficient machine learning models. A basic understanding of the machine learning concepts and some experience with Python programming is all you need to get started with this book.

Download or read book Introducing HR Analytics with Machine Learning written by Christopher M. Rosett and published by Springer Nature. This book was released on 2021-06-14 with total page 266 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book directly addresses the explosion of literature about leveraging analytics with employee data and how organizational psychologists and practitioners can harness new information to help guide positive change in the workplace. In order for today’s organizational psychologists to successfully work with their partners they must go beyond behavioral science into the realms of computing and business acumen. Similarly, today’s data scientists must appreciate the unique aspects of behavioral data and the special circumstances which surround HR data and HR systems. Finally, traditional HR professionals must become familiar with research methods, statistics, and data systems in order to collaborate with these new specialized partners and teams. Despite the increasing importance of this diversity of skill, many organizations are still unprepared to build teams with the comprehensive skills necessary to have high performing HR Analytics functions. And importantly, all these considerations are magnified by the introduction and acceleration of machine learning in HR. This book will serve as an introduction to these areas and provide guidance on building the connectivity across domains required to establish well-rounded skills for individuals and best practices for organizations when beginning to apply advanced analytics to workforce data. It will also introduce machine learning and where it fits within the larger HR Analytics framework by explaining many of its basic tenets and methodologies. By the end of the book, readers will understand the skills required to do advanced HR analytics well, as well as how to begin designing and applying machine learning within a larger human capital strategy.