Deep Active Learning

2017-09-12
Deep Active Learning

PDF Deep Active Learning Download

  • Author: Kayo Matsushita
  • Publisher: Springer
  • ISBN: 9811056609
  • Category : Education
  • Languages : en
  • Pages : 228

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

2021-07-20
Human-in-the-Loop Machine Learning

PDF Human-in-the-Loop Machine Learning Download

  • Author: Robert Munro
  • Publisher: Simon and Schuster
  • ISBN: 1617296740
  • Category : Computers
  • Languages : en
  • Pages : 422

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

2021-10-06
Active Learning Online

PDF Active Learning Online Download

  • Author: Stephen Kosslyn
  • Publisher:
  • ISBN: 9781735810744
  • Category :
  • Languages : en
  • Pages :

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

2021-05-21
How-to Guide for Active Learning

PDF How-to Guide for Active Learning Download

  • Author: Alice Fornari
  • Publisher: Springer Nature
  • ISBN: 3030629163
  • Category : Education
  • Languages : en
  • Pages : 150

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

2020-10-02
Medical Image Computing and Computer Assisted Intervention – MICCAI 2020

PDF Medical Image Computing and Computer Assisted Intervention – MICCAI 2020 Download

  • Author: Anne L. Martel
  • Publisher: Springer Nature
  • ISBN: 3030597105
  • Category : Computers
  • Languages : en
  • Pages : 886

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

Pattern Recognition and Artificial Intelligence

2020-10-09
Pattern Recognition and Artificial Intelligence

PDF Pattern Recognition and Artificial Intelligence Download

  • Author: Yue Lu
  • Publisher: Springer Nature
  • ISBN: 3030598306
  • Category : Computers
  • Languages : en
  • Pages : 752

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.

Minding American Education

2003-01-01
Minding American Education

PDF Minding American Education Download

  • Author: Martin Bickman
  • Publisher: Teachers College Press
  • ISBN: 0807743526
  • Category : Education
  • Languages : en
  • Pages : 193

This book presents an antidote to the self-destructive war between educational conservatives and progressives, arguing that each has only part of the solution in what should be a productive dialectic between experience and concepts--Outlines the rich tradition of educational thought we have already created in this country, suggesting ways to apply it to our current reform efforts--Provides a new paradigm for re-conceptualizing our educational past, urging us to move in the direction of our best and most characteristic literary and philosophical thinkers--Critiques the usual academic discourse on education and suggests alternatives through his lively and direct style.

Active Learning

1991
Active Learning

PDF Active Learning Download

  • Author: Charles C. Bonwell
  • Publisher:
  • ISBN:
  • Category :
  • Languages : en
  • Pages : 136

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)

Teaching with Classroom Response Systems

2009-10-22
Teaching with Classroom Response Systems

PDF Teaching with Classroom Response Systems Download

  • Author: Derek Bruff
  • Publisher: John Wiley & Sons
  • ISBN: 0470596619
  • Category : Education
  • Languages : en
  • Pages : 240

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

Introduction to Deep Learning

2019-01-29
Introduction to Deep Learning

PDF Introduction to Deep Learning Download

  • Author: Eugene Charniak
  • Publisher: MIT Press
  • ISBN: 0262039516
  • Category : Computers
  • Languages : en
  • Pages : 187

A project-based guide to the basics of deep learning. This concise, project-driven guide to deep learning takes readers through a series of program-writing tasks that introduce them to the use of deep learning in such areas of artificial intelligence as computer vision, natural-language processing, and reinforcement learning. The author, a longtime artificial intelligence researcher specializing in natural-language processing, covers feed-forward neural nets, convolutional neural nets, word embeddings, recurrent neural nets, sequence-to-sequence learning, deep reinforcement learning, unsupervised models, and other fundamental concepts and techniques. Students and practitioners learn the basics of deep learning by working through programs in Tensorflow, an open-source machine learning framework. “I find I learn computer science material best by sitting down and writing programs,” the author writes, and the book reflects this approach. Each chapter includes a programming project, exercises, and references for further reading. An early chapter is devoted to Tensorflow and its interface with Python, the widely used programming language. Familiarity with linear algebra, multivariate calculus, and probability and statistics is required, as is a rudimentary knowledge of programming in Python. The book can be used in both undergraduate and graduate courses; practitioners will find it an essential reference.