Deep Active Learning

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Deep Active Learning

Author : Kayo Matsushita
Publisher : Springer
Page : 226 pages
File Size : 45,9 Mb
Release : 2017-09-12
Category : Education
ISBN : 9789811056604

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Deep Active Learning by Kayo Matsushita Pdf

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

Author : Robert Munro,Robert Monarch
Publisher : Simon and Schuster
Page : 422 pages
File Size : 42,6 Mb
Release : 2021-07-20
Category : Computers
ISBN : 9781617296741

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Human-in-the-Loop Machine Learning by Robert Munro,Robert Monarch Pdf

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

Author : Stephen Kosslyn
Publisher : Unknown
Page : 120 pages
File Size : 41,9 Mb
Release : 2020-09-18
Category : Electronic
ISBN : 1735810703

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Active Learning Online by Stephen Kosslyn Pdf

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

Author : Alice Fornari,Ann Poznanski
Publisher : Springer Nature
Page : 150 pages
File Size : 41,9 Mb
Release : 2021-05-21
Category : Education
ISBN : 9783030629168

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How-to Guide for Active Learning by Alice Fornari,Ann Poznanski Pdf

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.

Active Learning

Author : Burr Settles
Publisher : Morgan & Claypool Publishers
Page : 117 pages
File Size : 47,9 Mb
Release : 2012
Category : Computers
ISBN : 9781608457250

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Active Learning by Burr Settles Pdf

Provides a general introduction to active learning. It outlines several scenarios in which queries might be formulated, and details many query selection algorithms which have been organised into four broad categories, or "query selection frameworks". The book also touches on some of the theoretical foundations of active learning, and concludes with an overview of the strengths and weaknesses of these approaches.

Deep Learning

Author : Michael Fullan,Joanne Quinn,Joanne McEachen
Publisher : Corwin Press
Page : 209 pages
File Size : 41,9 Mb
Release : 2017-11-06
Category : Education
ISBN : 9781506368597

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Deep Learning by Michael Fullan,Joanne Quinn,Joanne McEachen Pdf

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.

New Learning Paradigms in Soft Computing

Author : Lakhmi C. Jain,Janusz Kacprzyk
Publisher : Physica
Page : 477 pages
File Size : 53,9 Mb
Release : 2013-06-05
Category : Computers
ISBN : 9783790818031

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New Learning Paradigms in Soft Computing by Lakhmi C. Jain,Janusz Kacprzyk Pdf

Learning is a key issue in the analysis and design of all kinds of intelligent systems. In recent time many new paradigms of automated (machine) learning have been proposed in the literature. Soft computing, that has proved to be an effective and efficient tool in so many areas of science and technology, seems to offer new qualities in the realm of machine learning too. The purpose of this volume is to present some new learning paradigms that have been triggered, or at least strongly influenced by soft computing tools and techniques, mainly related to neural networks, fuzzy logic, rough sets, and evolutionary computations.

Medical Image Computing and Computer Assisted Intervention – MICCAI 2020

Author : Anne L. Martel,Purang Abolmaesumi,Danail Stoyanov,Diana Mateus,Maria A. Zuluaga,S. Kevin Zhou,Daniel Racoceanu,Leo Joskowicz
Publisher : Springer Nature
Page : 849 pages
File Size : 55,6 Mb
Release : 2020-10-02
Category : Computers
ISBN : 9783030597108

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Medical Image Computing and Computer Assisted Intervention – MICCAI 2020 by Anne L. Martel,Purang Abolmaesumi,Danail Stoyanov,Diana Mateus,Maria A. Zuluaga,S. Kevin Zhou,Daniel Racoceanu,Leo Joskowicz Pdf

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

Digital Pathology

Author : Constantino Carlos Reyes-Aldasoro,Andrew Janowczyk,Mitko Veta,Peter Bankhead,Korsuk Sirinukunwattana
Publisher : Springer
Page : 192 pages
File Size : 40,7 Mb
Release : 2019-07-03
Category : Computers
ISBN : 9783030239374

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Digital Pathology by Constantino Carlos Reyes-Aldasoro,Andrew Janowczyk,Mitko Veta,Peter Bankhead,Korsuk Sirinukunwattana Pdf

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.

Machine Learning in Non-Stationary Environments

Author : Masashi Sugiyama,Motoaki Kawanabe
Publisher : MIT Press
Page : 279 pages
File Size : 53,9 Mb
Release : 2012-03-30
Category : Computers
ISBN : 9780262300438

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Machine Learning in Non-Stationary Environments by Masashi Sugiyama,Motoaki Kawanabe Pdf

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.

Active Learning to Minimize the Possible Risk of Future Epidemics

Author : KC Santosh,Suprim Nakarmi
Publisher : Springer Nature
Page : 107 pages
File Size : 45,9 Mb
Release : 2023-12-24
Category : Technology & Engineering
ISBN : 9789819974429

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Active Learning to Minimize the Possible Risk of Future Epidemics by KC Santosh,Suprim Nakarmi Pdf

Future epidemics are inevitable, and it takes months and even years to collect fully annotated data. The sheer magnitude of data required for machine learning algorithms, spanning both shallow and deep structures, raises a fundamental question: how big data is big enough to effectively tackle future epidemics? In this context, active learning, often referred to as human or expert-in-the-loop learning, becomes imperative, enabling machines to commence learning from day one with minimal labeled data. In unsupervised learning, the focus shifts toward constructing advanced machine learning models like deep structured networks that autonomously learn over time, with human or expert intervention only when errors occur and for limited data—a process we term mentoring. In the context of Covid-19, this book explores the use of deep features to classify data into two clusters (0/1: Covid-19/non-Covid-19) across three distinct datasets: cough sound, Computed Tomography (CT) scan, and chest x-ray (CXR). Not to be confused, our primary objective is to provide a strong assertion on how active learning could potentially be used to predict disease from any upcoming epidemics. Upon request (education/training purpose), GitHub source codes are provided.

Teaching with Classroom Response Systems

Author : Derek Bruff
Publisher : John Wiley & Sons
Page : 240 pages
File Size : 43,6 Mb
Release : 2009-10-22
Category : Education
ISBN : 9780470596616

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Teaching with Classroom Response Systems by Derek Bruff Pdf

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

Active Learning

Author : Charles C. Bonwell,James A. Eison
Publisher : Unknown
Page : 136 pages
File Size : 52,5 Mb
Release : 1991
Category : Electronic
ISBN : 08840040

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Active Learning by Charles C. Bonwell,James A. Eison Pdf

This monograph examines the nature of active learning at the higher education level, the empirical research on its use, the common obstacles and barriers that give rise to faculty resistance, and how faculty and staff can implement active learning techniques. A preliminary section defines active learning and looks at the current climate surrounding the concept. A second section, entitled "The Modified Lecture" offers ways that teachers can incorporate active learning into their most frequently used format: the lecture. The following section on classroom discussion explains the conditions and techniques needed for the most useful type of exchange. Other ways to promote active learning are also described including: visual learning, writing in class, problem solving, computer-based instruction, cooperative learning, debates, drama, role playing, simulations, games, and peer teaching. A section on obstacles to implementing active learning techniques leads naturally to the final section, "Conclusions and Recommendations," which outlines the roles that each group within the university can play in order to encourage the implementation of active learning strategies. The text includes over 200 references and an index. (JB)

Deep Learning in Healthcare

Author : Yen-Wei Chen,Lakhmi C. Jain
Publisher : Springer Nature
Page : 225 pages
File Size : 55,8 Mb
Release : 2019-11-18
Category : Technology & Engineering
ISBN : 9783030326067

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Deep Learning in Healthcare by Yen-Wei Chen,Lakhmi C. Jain Pdf

This book provides a comprehensive overview of deep learning (DL) in medical and healthcare applications, including the fundamentals and current advances in medical image analysis, state-of-the-art DL methods for medical image analysis and real-world, deep learning-based clinical computer-aided diagnosis systems. Deep learning (DL) is one of the key techniques of artificial intelligence (AI) and today plays an important role in numerous academic and industrial areas. DL involves using a neural network with many layers (deep structure) between input and output, and its main advantage of is that it can automatically learn data-driven, highly representative and hierarchical features and perform feature extraction and classification on one network. DL can be used to model or simulate an intelligent system or process using annotated training data. Recently, DL has become widely used in medical applications, such as anatomic modelling, tumour detection, disease classification, computer-aided diagnosis and surgical planning. This book is intended for computer science and engineering students and researchers, medical professionals and anyone interested using DL techniques.

Data Classification

Author : Charu C. Aggarwal
Publisher : CRC Press
Page : 710 pages
File Size : 42,9 Mb
Release : 2014-07-25
Category : Business & Economics
ISBN : 9781498760584

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Data Classification by Charu C. Aggarwal Pdf

Comprehensive Coverage of the Entire Area of ClassificationResearch on the problem of classification tends to be fragmented across such areas as pattern recognition, database, data mining, and machine learning. Addressing the work of these different communities in a unified way, Data Classification: Algorithms and Applications explores the underlyi