Download or read book Strategies for Deep Learning with Digital Technology written by Robert Zheng and published by . This book was released on 2018 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book Strategies for Deep Learning with Digital Technology written by Robert Zheng and published by . This book was released on 2018 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: How to utilize digital technology to engage learners in deep learning is an issue that warrants significant attention in 21st century education. Deep learning refers to learners engagement in critical and creative thinking, making inferences and transferring knowledge. Modern technologies like virtual reality, artificial intelligence, and 3D visualization provide the platform for deep learning in an educational setting more effectively. This book presents a collection of essays on the relationship between digital technologies and deep learning. The edited volume focuses on cognitive, metacognitive and affective processes in digital technology-based deep learning. A unique feature of the book is its emphasis on bridging the theories with practice where the practice of deep learning with digital technology is well-grounded in relevant theories and theoretical frameworks. Moreover, the book includes case studies to effectively promote the application of digital technology in deep learning. As such, the book is rightly poised to address current issues facing deep learning and digital technology in education. The audience will find this book a useful companion as they will soon discover that this book provides helpful information on both theoretical and practical aspects in deep learning with digital technology. It also serves as an excellent resource for researchers and individual professionals who seek to understand the relationship between deep learning and digital technology in education.
Download or read book Getting Smart written by Tom Vander Ark and published by John Wiley & Sons. This book was released on 2011-09-20 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive look at the promise and potential of online learning In our digital age, students have dramatically new learning needs and must be prepared for the idea economy of the future. In Getting Smart, well-known global education expert Tom Vander Ark examines the facets of educational innovation in the United States and abroad. Vander Ark makes a convincing case for a blend of online and onsite learning, shares inspiring stories of schools and programs that effectively offer "personal digital learning" opportunities, and discusses what we need to do to remake our schools into "smart schools." Examines the innovation-driven world, discusses how to combine online and onsite learning, and reviews "smart tools" for learning Investigates the lives of learning professionals, outlines the new employment bargain, examines online universities and "smart schools" Makes the case for smart capital, advocates for policies that create better learning, studies smart cultures
Download or read book Deep Learning written by Michael Fullan and published by Corwin Press. This book was released on 2017-11-06 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: New Pedagogies for Deep Learning (NDPL) provides a comprehensive strategy for systemwide transformation. Using the 6 competencies of NDPL and a wealth of vivid examples, Fullan re-defines and re-examines what deep learning is and identifies the practical strategies for revolutionizing learning and leadership.
Download or read book Artificial Intelligence and Deep Learning in Pathology written by Stanley Cohen and published by Elsevier Health Sciences. This book was released on 2020-06-02 with total page 290 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recent advances in computational algorithms, along with the advent of whole slide imaging as a platform for embedding artificial intelligence (AI), are transforming pattern recognition and image interpretation for diagnosis and prognosis. Yet most pathologists have just a passing knowledge of data mining, machine learning, and AI, and little exposure to the vast potential of these powerful new tools for medicine in general and pathology in particular. In Artificial Intelligence and Deep Learning in Pathology, Dr. Stanley Cohen covers the nuts and bolts of all aspects of machine learning, up to and including AI, bringing familiarity and understanding to pathologists at all levels of experience. - Focuses heavily on applications in medicine, especially pathology, making unfamiliar material accessible and avoiding complex mathematics whenever possible. - Covers digital pathology as a platform for primary diagnosis and augmentation via deep learning, whole slide imaging for 2D and 3D analysis, and general principles of image analysis and deep learning. - Discusses and explains recent accomplishments such as algorithms used to diagnose skin cancer from photographs, AI-based platforms developed to identify lesions of the retina, using computer vision to interpret electrocardiograms, identifying mitoses in cancer using learning algorithms vs. signal processing algorithms, and many more.
Download or read book The Deep Learning Revolution written by Terrence J. Sejnowski and published by MIT Press. This book was released on 2018-10-23 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: How deep learning—from Google Translate to driverless cars to personal cognitive assistants—is changing our lives and transforming every sector of the economy. The deep learning revolution has brought us driverless cars, the greatly improved Google Translate, fluent conversations with Siri and Alexa, and enormous profits from automated trading on the New York Stock Exchange. Deep learning networks can play poker better than professional poker players and defeat a world champion at Go. In this book, Terry Sejnowski explains how deep learning went from being an arcane academic field to a disruptive technology in the information economy. Sejnowski played an important role in the founding of deep learning, as one of a small group of researchers in the 1980s who challenged the prevailing logic-and-symbol based version of AI. The new version of AI Sejnowski and others developed, which became deep learning, is fueled instead by data. Deep networks learn from data in the same way that babies experience the world, starting with fresh eyes and gradually acquiring the skills needed to navigate novel environments. Learning algorithms extract information from raw data; information can be used to create knowledge; knowledge underlies understanding; understanding leads to wisdom. Someday a driverless car will know the road better than you do and drive with more skill; a deep learning network will diagnose your illness; a personal cognitive assistant will augment your puny human brain. It took nature many millions of years to evolve human intelligence; AI is on a trajectory measured in decades. Sejnowski prepares us for a deep learning future.
Download or read book Deep Learning Techniques and Optimization Strategies in Big Data Analytics written by Thomas, J. Joshua and published by IGI Global. This book was released on 2019-11-29 with total page 355 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many approaches have sprouted from artificial intelligence (AI) and produced major breakthroughs in the computer science and engineering industries. Deep learning is a method that is transforming the world of data and analytics. Optimization of this new approach is still unclear, however, and there’s a need for research on the various applications and techniques of deep learning in the field of computing. Deep Learning Techniques and Optimization Strategies in Big Data Analytics is a collection of innovative research on the methods and applications of deep learning strategies in the fields of computer science and information systems. While highlighting topics including data integration, computational modeling, and scheduling systems, this book is ideally designed for engineers, IT specialists, data analysts, data scientists, engineers, researchers, academicians, and students seeking current research on deep learning methods and its application in the digital industry.
Download or read book Harnessing Technology for Deeper Learning written by Scott McLeod and published by Solutions for Creating the Lea. This book was released on 2018-09-21 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: "By embracing technology in the classroom instead of ignorning or banning it, every educator can promote deeper learning across all subjects and grade levels. Using the 4 Shifts Protocol, 'Harnessing Technology for Deeper Learning' imparts valuable strategies for avoiding missteps, overcoming implemention challenges, and (re)designing instruction that is both meaningful and engaging".
Download or read book Examining the Impact of Deep Learning and IoT on Multi Industry Applications written by Raut, Roshani and published by IGI Global. This book was released on 2021-01-29 with total page 304 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep learning, as a recent AI technique, has proven itself efficient in solving many real-world problems. Deep learning algorithms are efficient, high performing, and an effective standard for solving these problems. In addition, with IoT, deep learning is in many emerging and developing domains of computer technology. Deep learning algorithms have brought a revolution in computer vision applications by introducing an efficient solution to several image processing-related problems that have long remained unresolved or moderately solved. Various significant IoT technologies in various industries, such as education, health, transportation, and security, combine IoT with deep learning for complex problem solving and the supported interaction between human beings and their surroundings. Examining the Impact of Deep Learning and IoT on Multi-Industry Applications provides insights on how deep learning, together with IoT, impacts various sectors such as healthcare, agriculture, cyber security, and social media analysis applications. The chapters present solutions to various real-world problems using these methods from various researchers’ points of view. While highlighting topics such as medical diagnosis, power consumption, livestock management, security, and social media analysis, this book is ideal for IT specialists, technologists, security analysts, medical practitioners, imaging specialists, diagnosticians, academicians, researchers, industrial experts, scientists, and undergraduate and postgraduate students who are working in the field of computer engineering, electronics, and electrical engineering.
Download or read book Deep Learning in Adaptive Learning Educational Behavior and Strategy written by Chia-Chen Chen and published by Frontiers Media SA. This book was released on 2022-09-14 with total page 652 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Download or read book The Deep Learning AI Playbook written by Carlos Perez and published by Lulu.com. This book was released on 2017-10-11 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Just like any new technology, what perplexes many is the question of how to apply Deep Learning in a business context. Technology that is disruptive does not automatically imply that the development of valuable use cases are apparent. For years, many people could not figure out how to monetize the World Wide Web. We are in that same situation with Deep Learning AI. The developments are mind-boggling but the monetization is far from being obvious.Deep Learning Artificial Intelligence involves the interplay of Computer Science, Physics, Biology, Linguistics and Psychology. In addition to that, it is technology that can be extremely disruptive. Furthermore, the ramifications to society and even our own humanity can be immense. There are few subjects that are as captivating and as consequential as this. Surprisingly, there is very little that is written about this new technology in a more comprehensive and cohesive way. This book is an opinionated take on the developments of Deep Learning AI.
Download or read book Digital Technologies in Teaching and Learning Strategies written by Alexandr Lyapin and published by Springer Nature. This book was released on 2022-05-03 with total page 288 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book demonstrates the benefits and drawbacks of using digital technology in preparing online lessons and educational activities. The experience of the last year has shown that online education is becoming a priority. This gave impetus to the creation and development of a new generation of equipment for online education. The book presents latest innovative technologies and modern digital trends in the field of information and communication technology for online education, including personalized learning, neuro-information systems, mobile learning, development of software and hardware infrastructure, and the use of robotics technologies. Key technologies for managing risk and cybersecurity, such as cloud and data security, identity and trust convolution systems, computational intelligence and cryptography techniques, malware and attack analysis, are presented. The topic of cybersecurity is one of the most important issues in the modern digital world. The results of the research on recently developed software, decision support systems, and cloud technologies make a huge contribution to the development of information technology in the context of digitalization. This book is of interest for developers of applications and programs for online education, for software and hardware suppliers who want to keep up with the times and reorient existing IT systems for use in online education.
Download or read book OECD Digital Education Outlook 2021 Pushing the Frontiers with Artificial Intelligence Blockchain and Robots written by OECD and published by OECD Publishing. This book was released on 2021-06-08 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: How might digital technology and notably smart technologies based on artificial intelligence (AI), learning analytics, robotics, and others transform education? This book explores such question. It focuses on how smart technologies currently change education in the classroom and the management of educational organisations and systems.
Download or read book Teacher Education in the 21st Century written by Maria Jose Hernández-Serrano and published by BoD – Books on Demand. This book was released on 2021-06-16 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the face of unprecedented disruption from the COVID-19 pandemic and the rapid acceleration of digital technologies, it is necessary to rethink the competences required by teachers for meeting new and flexible learning demands. Teacher training is an area constantly evolving along with emerging social challenges that are transforming educational institutions and agents. This book provides teachers with skills, innovative solutions, cutting-edge studies, and methodologies to meet education and training system demands. In our changing world, preparing teachers worldwide for the challenges and shifts of this era involves the opportunity to exchange theories, practices, and experiences such as those contained in this book.
Download or read book How People Learn II written by National Academies of Sciences, Engineering, and Medicine and published by National Academies Press. This book was released on 2018-09-27 with total page 347 pages. Available in PDF, EPUB and Kindle. Book excerpt: There are many reasons to be curious about the way people learn, and the past several decades have seen an explosion of research that has important implications for individual learning, schooling, workforce training, and policy. In 2000, How People Learn: Brain, Mind, Experience, and School: Expanded Edition was published and its influence has been wide and deep. The report summarized insights on the nature of learning in school-aged children; described principles for the design of effective learning environments; and provided examples of how that could be implemented in the classroom. Since then, researchers have continued to investigate the nature of learning and have generated new findings related to the neurological processes involved in learning, individual and cultural variability related to learning, and educational technologies. In addition to expanding scientific understanding of the mechanisms of learning and how the brain adapts throughout the lifespan, there have been important discoveries about influences on learning, particularly sociocultural factors and the structure of learning environments. How People Learn II: Learners, Contexts, and Cultures provides a much-needed update incorporating insights gained from this research over the past decade. The book expands on the foundation laid out in the 2000 report and takes an in-depth look at the constellation of influences that affect individual learning. How People Learn II will become an indispensable resource to understand learning throughout the lifespan for educators of students and adults.
Download or read book The Deep Learning AI Playbook written by Carlos Perez and published by Createspace Independent Publishing Platform. This book was released on 2017-10-11 with total page 352 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning Artificial Intelligence involves the interplay of Computer Science, Physics, Biology, Linguistics and Psychology. In addition to that, it is technology that can be extremely disruptive. The ramifications to society and even our own humanity will be profound. There are few subjects that are as captivating and as consequential as this. Surprisingly, there is very little that is written about this new technology in a more comprehensive and cohesive way. This book is an opinionated take on the developments of Deep Learning AI. One question many have will be "how to apply Deep Learning AI in a business context?" Technology that is disruptive does not automatically imply that its application to valuable use cases will be apparent. For years, many people could not figure out how to monetize the World Wide Web. We are in a similar situation with Deep Learning AI. The developments may be mind-boggling but its monetization is far from being obvious. This book presents a framework to address this shortcoming.
Download or read book Deep Learning written by Ian Goodfellow and published by MIT Press. This book was released on 2016-11-10 with total page 801 pages. Available in PDF, EPUB and Kindle. Book excerpt: An introduction to a broad range of topics in deep learning, covering mathematical and conceptual background, deep learning techniques used in industry, and research perspectives. “Written by three experts in the field, Deep Learning is the only comprehensive book on the subject.” —Elon Musk, cochair of OpenAI; cofounder and CEO of Tesla and SpaceX Deep learning is a form of machine learning that enables computers to learn from experience and understand the world in terms of a hierarchy of concepts. Because the computer gathers knowledge from experience, there is no need for a human computer operator to formally specify all the knowledge that the computer needs. The hierarchy of concepts allows the computer to learn complicated concepts by building them out of simpler ones; a graph of these hierarchies would be many layers deep. This book introduces a broad range of topics in deep learning. The text offers mathematical and conceptual background, covering relevant concepts in linear algebra, probability theory and information theory, numerical computation, and machine learning. It describes deep learning techniques used by practitioners in industry, including deep feedforward networks, regularization, optimization algorithms, convolutional networks, sequence modeling, and practical methodology; and it surveys such applications as natural language processing, speech recognition, computer vision, online recommendation systems, bioinformatics, and videogames. Finally, the book offers research perspectives, covering such theoretical topics as linear factor models, autoencoders, representation learning, structured probabilistic models, Monte Carlo methods, the partition function, approximate inference, and deep generative models. Deep Learning can be used by undergraduate or graduate students planning careers in either industry or research, and by software engineers who want to begin using deep learning in their products or platforms. A website offers supplementary material for both readers and instructors.
