Deep Active Learning

Deep Active Learning

Author: Kayo Matsushita

Publisher: Springer

Published: 2017-09-12

Total Pages: 226

ISBN-13: 9811056609

DOWNLOAD EBOOK

This is the first book to connect the concepts of active learning and deep learning, and to delineate theory and practice through collaboration between scholars in higher education from three countries (Japan, the United States, and Sweden) as well as different subject areas (education, psychology, learning science, teacher training, dentistry, and business).It is only since the beginning of the twenty-first century that active learning has become key to the shift from teaching to learning in Japanese higher education. However, “active learning” in Japan, as in many other countries, is just an umbrella term for teaching methods that promote students’ active participation, such as group work, discussions, presentations, and so on.What is needed for students is not just active learning but deep active learning. Deep learning focuses on content and quality of learning whereas active learning, especially in Japan, focuses on methods of learning. Deep active learning is placed at the intersection of active learning and deep learning, referring to learning that engages students with the world as an object of learning while interacting with others, and helps the students connect what they are learning with their previous knowledge and experiences as well as their future lives.What curricula, pedagogies, assessments and learning environments facilitate such deep active learning? This book attempts to respond to that question by linking theory with practice.


Book Synopsis Deep Active Learning by : Kayo Matsushita

Download or read book Deep Active Learning written by Kayo Matsushita and published by Springer. This book was released on 2017-09-12 with total page 226 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is the first book to connect the concepts of active learning and deep learning, and to delineate theory and practice through collaboration between scholars in higher education from three countries (Japan, the United States, and Sweden) as well as different subject areas (education, psychology, learning science, teacher training, dentistry, and business).It is only since the beginning of the twenty-first century that active learning has become key to the shift from teaching to learning in Japanese higher education. However, “active learning” in Japan, as in many other countries, is just an umbrella term for teaching methods that promote students’ active participation, such as group work, discussions, presentations, and so on.What is needed for students is not just active learning but deep active learning. Deep learning focuses on content and quality of learning whereas active learning, especially in Japan, focuses on methods of learning. Deep active learning is placed at the intersection of active learning and deep learning, referring to learning that engages students with the world as an object of learning while interacting with others, and helps the students connect what they are learning with their previous knowledge and experiences as well as their future lives.What curricula, pedagogies, assessments and learning environments facilitate such deep active learning? This book attempts to respond to that question by linking theory with practice.


Human-in-the-Loop Machine Learning

Human-in-the-Loop Machine Learning

Author: Robert Munro

Publisher: Simon and Schuster

Published: 2021-07-20

Total Pages: 422

ISBN-13: 1617296740

DOWNLOAD EBOOK

Machine learning applications perform better with human feedback. Keeping the right people in the loop improves the accuracy of models, reduces errors in data, lowers costs, and helps you ship models faster. Human-in-the-loop machine learning lays out methods for humans and machines to work together effectively. You'll find best practices on selecting sample data for human feedback, quality control for human annotations, and designing annotation interfaces. You'll learn to dreate training data for labeling, object detection, and semantic segmentation, sequence labeling, and more. The book starts with the basics and progresses to advanced techniques like transfer learning and self-supervision within annotation workflows.


Book Synopsis Human-in-the-Loop Machine Learning by : Robert Munro

Download or read book Human-in-the-Loop Machine Learning written by Robert Munro and published by Simon and Schuster. This book was released on 2021-07-20 with total page 422 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning applications perform better with human feedback. Keeping the right people in the loop improves the accuracy of models, reduces errors in data, lowers costs, and helps you ship models faster. Human-in-the-loop machine learning lays out methods for humans and machines to work together effectively. You'll find best practices on selecting sample data for human feedback, quality control for human annotations, and designing annotation interfaces. You'll learn to dreate training data for labeling, object detection, and semantic segmentation, sequence labeling, and more. The book starts with the basics and progresses to advanced techniques like transfer learning and self-supervision within annotation workflows.


Active Learning Online

Active Learning Online

Author: Stephen Kosslyn

Publisher:

Published: 2020-09-18

Total Pages: 120

ISBN-13: 9781735810706

DOWNLOAD EBOOK

Inspired by the recent proliferation of online courses necessitated by the COVID 19 pandemic, researcher and educational innovator Stephen M. Kosslyn offers instructors and course designers (as well as school administrations and teacher-education students) a treasure trove of active learning principles and activities for implementation in online, hybrid and in-person courses. Whether your course is synchronous (e.g., live with Zoom) or asynchronous (e.g., using video content on Canvas), this book will inject active learning into existing courses or into courses designed from scratch. In both cases, active learning will make the courses not only more interesting but also more effective; student engagement will increase, learning outcomes will be reached, and general teaching and learning experiences will be enriched.


Book Synopsis Active Learning Online by : Stephen Kosslyn

Download or read book Active Learning Online written by Stephen Kosslyn and published by . This book was released on 2020-09-18 with total page 120 pages. Available in PDF, EPUB and Kindle. Book excerpt: Inspired by the recent proliferation of online courses necessitated by the COVID 19 pandemic, researcher and educational innovator Stephen M. Kosslyn offers instructors and course designers (as well as school administrations and teacher-education students) a treasure trove of active learning principles and activities for implementation in online, hybrid and in-person courses. Whether your course is synchronous (e.g., live with Zoom) or asynchronous (e.g., using video content on Canvas), this book will inject active learning into existing courses or into courses designed from scratch. In both cases, active learning will make the courses not only more interesting but also more effective; student engagement will increase, learning outcomes will be reached, and general teaching and learning experiences will be enriched.


How-to Guide for Active Learning

How-to Guide for Active Learning

Author: Alice Fornari

Publisher: Springer Nature

Published: 2021-05-21

Total Pages: 150

ISBN-13: 3030629163

DOWNLOAD EBOOK

This book focuses on large and small group educational settings and offers brief strategies to engage learners to assure active learning strategies are core to the learning environment. The book opens with an introduction on active learning principles. Each chapter follows with a specific description of a strategy written by authors who are experienced in using the strategy in a classroom environment with students. The chapters are designed to be accessible and practical for the reader to apply in their learning environments.


Book Synopsis How-to Guide for Active Learning by : Alice Fornari

Download or read book How-to Guide for Active Learning written by Alice Fornari and published by Springer Nature. This book was released on 2021-05-21 with total page 150 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on large and small group educational settings and offers brief strategies to engage learners to assure active learning strategies are core to the learning environment. The book opens with an introduction on active learning principles. Each chapter follows with a specific description of a strategy written by authors who are experienced in using the strategy in a classroom environment with students. The chapters are designed to be accessible and practical for the reader to apply in their learning environments.


Medical Image Computing and Computer Assisted Intervention – MICCAI 2020

Medical Image Computing and Computer Assisted Intervention – MICCAI 2020

Author: Anne L. Martel

Publisher: Springer Nature

Published: 2020-10-02

Total Pages: 849

ISBN-13: 3030597105

DOWNLOAD EBOOK

The seven-volume set LNCS 12261, 12262, 12263, 12264, 12265, 12266, and 12267 constitutes the refereed proceedings of the 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020, held in Lima, Peru, in October 2020. The conference was held virtually due to the COVID-19 pandemic. The 542 revised full papers presented were carefully reviewed and selected from 1809 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: machine learning methodologies Part II: image reconstruction; prediction and diagnosis; cross-domain methods and reconstruction; domain adaptation; machine learning applications; generative adversarial networks Part III: CAI applications; image registration; instrumentation and surgical phase detection; navigation and visualization; ultrasound imaging; video image analysis Part IV: segmentation; shape models and landmark detection Part V: biological, optical, microscopic imaging; cell segmentation and stain normalization; histopathology image analysis; opthalmology Part VI: angiography and vessel analysis; breast imaging; colonoscopy; dermatology; fetal imaging; heart and lung imaging; musculoskeletal imaging Part VI: brain development and atlases; DWI and tractography; functional brain networks; neuroimaging; positron emission tomography


Book Synopsis Medical Image Computing and Computer Assisted Intervention – MICCAI 2020 by : Anne L. Martel

Download or read book Medical Image Computing and Computer Assisted Intervention – MICCAI 2020 written by Anne L. Martel and published by Springer Nature. This book was released on 2020-10-02 with total page 849 pages. Available in PDF, EPUB and Kindle. Book excerpt: The seven-volume set LNCS 12261, 12262, 12263, 12264, 12265, 12266, and 12267 constitutes the refereed proceedings of the 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2020, held in Lima, Peru, in October 2020. The conference was held virtually due to the COVID-19 pandemic. The 542 revised full papers presented were carefully reviewed and selected from 1809 submissions in a double-blind review process. The papers are organized in the following topical sections: Part I: machine learning methodologies Part II: image reconstruction; prediction and diagnosis; cross-domain methods and reconstruction; domain adaptation; machine learning applications; generative adversarial networks Part III: CAI applications; image registration; instrumentation and surgical phase detection; navigation and visualization; ultrasound imaging; video image analysis Part IV: segmentation; shape models and landmark detection Part V: biological, optical, microscopic imaging; cell segmentation and stain normalization; histopathology image analysis; opthalmology Part VI: angiography and vessel analysis; breast imaging; colonoscopy; dermatology; fetal imaging; heart and lung imaging; musculoskeletal imaging Part VI: brain development and atlases; DWI and tractography; functional brain networks; neuroimaging; positron emission tomography


Teaching with Classroom Response Systems

Teaching with Classroom Response Systems

Author: Derek Bruff

Publisher: John Wiley & Sons

Published: 2009-10-22

Total Pages: 240

ISBN-13: 0470596619

DOWNLOAD EBOOK

There is a need in the higher education arena for a book that responds to the need for using technology in a classroom of tech-savvy students. This book is filled with illustrative examples of questions and teaching activities that use classroom response systems from a variety of disciplines (with a discipline index). The book also incorporates results from research on the effectiveness of the technology for teaching. Written for instructional designers and re-designers as well as faculty across disciplines. A must-read for anyone interested in interactive teaching and the use of clickers. This book draws on the experiences of countless instructors across a wide range of disciplines to provide both novice and experienced teachers with practical advice on how to make classes more fun and more effective.”--Eric Mazur, Balkanski Professor of Physics and Applied Physics, Harvard University, and author, Peer Instruction: A User’s Manual “Those who come to this book needing practical advice on using ‘clickers’ in the classroom will be richly rewarded: with case studies, a refreshing historical perspective, and much pedagogical ingenuity. Those who seek a deep, thoughtful examination of strategies for active learning will find that here as well—in abundance. Dr. Bruff achieves a marvelous synthesis of the pragmatic and the philosophical that will be useful far beyond the life span of any single technology.” --Gardner Campbell, Director, Academy for Teaching and Learning, and Associate Professor of Literature, Media, and Learning, Honors College, Baylor University


Book Synopsis Teaching with Classroom Response Systems by : Derek Bruff

Download or read book Teaching with Classroom Response Systems written by Derek Bruff and published by John Wiley & Sons. This book was released on 2009-10-22 with total page 240 pages. Available in PDF, EPUB and Kindle. Book excerpt: There is a need in the higher education arena for a book that responds to the need for using technology in a classroom of tech-savvy students. This book is filled with illustrative examples of questions and teaching activities that use classroom response systems from a variety of disciplines (with a discipline index). The book also incorporates results from research on the effectiveness of the technology for teaching. Written for instructional designers and re-designers as well as faculty across disciplines. A must-read for anyone interested in interactive teaching and the use of clickers. This book draws on the experiences of countless instructors across a wide range of disciplines to provide both novice and experienced teachers with practical advice on how to make classes more fun and more effective.”--Eric Mazur, Balkanski Professor of Physics and Applied Physics, Harvard University, and author, Peer Instruction: A User’s Manual “Those who come to this book needing practical advice on using ‘clickers’ in the classroom will be richly rewarded: with case studies, a refreshing historical perspective, and much pedagogical ingenuity. Those who seek a deep, thoughtful examination of strategies for active learning will find that here as well—in abundance. Dr. Bruff achieves a marvelous synthesis of the pragmatic and the philosophical that will be useful far beyond the life span of any single technology.” --Gardner Campbell, Director, Academy for Teaching and Learning, and Associate Professor of Literature, Media, and Learning, Honors College, Baylor University


Digital Pathology

Digital Pathology

Author: Constantino Carlos Reyes-Aldasoro

Publisher: Springer

Published: 2019-07-03

Total Pages: 192

ISBN-13: 3030239373

DOWNLOAD EBOOK

This book constitutes the refereed proceedings of the 15th European Congress on Digital Pathology, ECDP 2019, held in Warwick, UK in April 2019. The 21 full papers presented in this volume were carefully reviewed and selected from 30 submissions. The congress theme will be Accelerating Clinical Deployment, with a focus on computational pathology and leveraging the power of big data and artificial intelligence to bridge the gaps between research, development, and clinical uptake.


Book Synopsis Digital Pathology by : Constantino Carlos Reyes-Aldasoro

Download or read book Digital Pathology written by Constantino Carlos Reyes-Aldasoro and published by Springer. This book was released on 2019-07-03 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 15th European Congress on Digital Pathology, ECDP 2019, held in Warwick, UK in April 2019. The 21 full papers presented in this volume were carefully reviewed and selected from 30 submissions. The congress theme will be Accelerating Clinical Deployment, with a focus on computational pathology and leveraging the power of big data and artificial intelligence to bridge the gaps between research, development, and clinical uptake.


Pattern Recognition and Artificial Intelligence

Pattern Recognition and Artificial Intelligence

Author: Yue Lu

Publisher: Springer

Published: 2020-09-23

Total Pages: 0

ISBN-13: 9783030598297

DOWNLOAD EBOOK

This book constitutes the proceedings of the Second International Conference on Pattern Recognition and Artificial Intelligence, ICPRAI 2020, which took place in Zhongshan, China, in October 2020. The 49 full and 14 short papers presented were carefully reviewed and selected for inclusion in the book. The papers were organized in topical sections as follows: handwriting and text processing; features and classifiers; deep learning; computer vision and image processing; medical imaging and applications; and forensic studies and medical diagnosis.


Book Synopsis Pattern Recognition and Artificial Intelligence by : Yue Lu

Download or read book Pattern Recognition and Artificial Intelligence written by Yue Lu and published by Springer. This book was released on 2020-09-23 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the Second International Conference on Pattern Recognition and Artificial Intelligence, ICPRAI 2020, which took place in Zhongshan, China, in October 2020. The 49 full and 14 short papers presented were carefully reviewed and selected for inclusion in the book. The papers were organized in topical sections as follows: handwriting and text processing; features and classifiers; deep learning; computer vision and image processing; medical imaging and applications; and forensic studies and medical diagnosis.


Deep Learning

Deep Learning

Author: Michael Fullan

Publisher: Corwin Press

Published: 2017-11-06

Total Pages: 209

ISBN-13: 150636859X

DOWNLOAD EBOOK

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.


Book Synopsis Deep Learning by : Michael Fullan

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.


Machine Learning in Non-Stationary Environments

Machine Learning in Non-Stationary Environments

Author: Masashi Sugiyama

Publisher: MIT Press

Published: 2012-03-30

Total Pages: 279

ISBN-13: 0262300435

DOWNLOAD EBOOK

Theory, algorithms, and applications of machine learning techniques to overcome “covariate shift” non-stationarity. As the power of computing has grown over the past few decades, the field of machine learning has advanced rapidly in both theory and practice. Machine learning methods are usually based on the assumption that the data generation mechanism does not change over time. Yet real-world applications of machine learning, including image recognition, natural language processing, speech recognition, robot control, and bioinformatics, often violate this common assumption. Dealing with non-stationarity is one of modern machine learning's greatest challenges. This book focuses on a specific non-stationary environment known as covariate shift, in which the distributions of inputs (queries) change but the conditional distribution of outputs (answers) is unchanged, and presents machine learning theory, algorithms, and applications to overcome this variety of non-stationarity. After reviewing the state-of-the-art research in the field, the authors discuss topics that include learning under covariate shift, model selection, importance estimation, and active learning. They describe such real world applications of covariate shift adaption as brain-computer interface, speaker identification, and age prediction from facial images. With this book, they aim to encourage future research in machine learning, statistics, and engineering that strives to create truly autonomous learning machines able to learn under non-stationarity.


Book Synopsis Machine Learning in Non-Stationary Environments by : Masashi Sugiyama

Download or read book Machine Learning in Non-Stationary Environments written by Masashi Sugiyama and published by MIT Press. This book was released on 2012-03-30 with total page 279 pages. Available in PDF, EPUB and Kindle. Book excerpt: Theory, algorithms, and applications of machine learning techniques to overcome “covariate shift” non-stationarity. As the power of computing has grown over the past few decades, the field of machine learning has advanced rapidly in both theory and practice. Machine learning methods are usually based on the assumption that the data generation mechanism does not change over time. Yet real-world applications of machine learning, including image recognition, natural language processing, speech recognition, robot control, and bioinformatics, often violate this common assumption. Dealing with non-stationarity is one of modern machine learning's greatest challenges. This book focuses on a specific non-stationary environment known as covariate shift, in which the distributions of inputs (queries) change but the conditional distribution of outputs (answers) is unchanged, and presents machine learning theory, algorithms, and applications to overcome this variety of non-stationarity. After reviewing the state-of-the-art research in the field, the authors discuss topics that include learning under covariate shift, model selection, importance estimation, and active learning. They describe such real world applications of covariate shift adaption as brain-computer interface, speaker identification, and age prediction from facial images. With this book, they aim to encourage future research in machine learning, statistics, and engineering that strives to create truly autonomous learning machines able to learn under non-stationarity.