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Author : Ian Goodfellow
Yoshua Bengio
Publisher : MIT Press
Release : 2016-11-10
Page : 800
Category : Computers
ISBN 13 : 0262337371
Description :


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.


Author : Richard S. Sutton
Andrew G. Barto
Publisher : MIT Press
Release : 2018-11-13
Page : 552
Category : Computers
ISBN 13 : 0262352702
Description :


The significantly expanded and updated new edition of a widely used text on reinforcement learning, one of the most active research areas in artificial intelligence. Reinforcement learning, one of the most active research areas in artificial intelligence, is a computational approach to learning whereby an agent tries to maximize the total amount of reward it receives while interacting with a complex, uncertain environment. In Reinforcement Learning, Richard Sutton and Andrew Barto provide a clear and simple account of the field's key ideas and algorithms. This second edition has been significantly expanded and updated, presenting new topics and updating coverage of other topics. Like the first edition, this second edition focuses on core online learning algorithms, with the more mathematical material set off in shaded boxes. Part I covers as much of reinforcement learning as possible without going beyond the tabular case for which exact solutions can be found. Many algorithms presented in this part are new to the second edition, including UCB, Expected Sarsa, and Double Learning. Part II extends these ideas to function approximation, with new sections on such topics as artificial neural networks and the Fourier basis, and offers expanded treatment of off-policy learning and policy-gradient methods. Part III has new chapters on reinforcement learning's relationships to psychology and neuroscience, as well as an updated case-studies chapter including AlphaGo and AlphaGo Zero, Atari game playing, and IBM Watson's wagering strategy. The final chapter discusses the future societal impacts of reinforcement learning.


Author : Trevor Hastie
Robert Tibshirani
Publisher : Springer Science & Business Media
Release : 2013-11-11
Page : 536
Category : Mathematics
ISBN 13 : 0387216065
Description :


During the past decade there has been an explosion in computation and information technology. With it have come vast amounts of data in a variety of fields such as medicine, biology, finance, and marketing. The challenge of understanding these data has led to the development of new tools in the field of statistics, and spawned new areas such as data mining, machine learning, and bioinformatics. Many of these tools have common underpinnings but are often expressed with different terminology. This book describes the important ideas in these areas in a common conceptual framework. While the approach is statistical, the emphasis is on concepts rather than mathematics. Many examples are given, with a liberal use of color graphics. It should be a valuable resource for statisticians and anyone interested in data mining in science or industry. The book’s coverage is broad, from supervised learning (prediction) to unsupervised learning. The many topics include neural networks, support vector machines, classification trees and boosting---the first comprehensive treatment of this topic in any book. This major new edition features many topics not covered in the original, including graphical models, random forests, ensemble methods, least angle regression & path algorithms for the lasso, non-negative matrix factorization, and spectral clustering. There is also a chapter on methods for “wide” data (p bigger than n), including multiple testing and false discovery rates. Trevor Hastie, Robert Tibshirani, and Jerome Friedman are professors of statistics at Stanford University. They are prominent researchers in this area: Hastie and Tibshirani developed generalized additive models and wrote a popular book of that title. Hastie co-developed much of the statistical modeling software and environment in R/S-PLUS and invented principal curves and surfaces. Tibshirani proposed the lasso and is co-author of the very successful An Introduction to the Bootstrap. Friedman is the co-inventor of many data-mining tools including CART, MARS, projection pursuit and gradient boosting.


Author : Christoph Molnar
Publisher : Lulu.com
Release : 2019
Page : 314
Category :
ISBN 13 : 0244768528
Description :



Author : Ronald R. Sims
Serbrenia J. Sims
Publisher : Greenwood Publishing Group
Release : 1995
Page : 216
Category : Education
ISBN 13 : 9780313292781
Description :


Brings together key research and examples for improved learning styles.


Author : Edward Swick
Publisher : Simon and Schuster
Release : 2013-07-18
Page : 256
Category : Foreign Language Study
ISBN 13 : 1440567581
Description :


Learn to speak and write German like a pro! Need a quick introduction to the German language? Whether you're planning a vacation, adding a valuable second language to your resume, or simply brushing up on your skills, The Everything Essential German Book is your perfect guide for learning to speak and write in German. This portable guide covers the most important basics, including: The German alphabet and translation Greetings and conversation starters Common questions and answers Verb tenses and sentence structure With step-by-step instructions, pronunciation guides, and practical exercises, you'll find learning German can be easy and fun! You'll be speaking--and understanding--German in no time!


Author : Dianne Conrad
Jason Openo
Publisher : Athabasca University Press
Release : 2018-07-15
Page : 212
Category : Education
ISBN 13 : 1771992328
Description :


Assessment has provided educational institutions with information about student learning outcomes and the quality of education for many decades. But has it informed practice and been fully incorporated into the learning cycle? Conrad and Openo argue that the potential inherent in many of the new learning environments being explored by educators and students has not been fully realized. In this investigation of a variety of assessment methods and learning approaches, the authors aim to discover the tools that engage learners and authentically evaluate education. They insist that moving to new learning environments, specifically those online and at a distance, afford opportunities for educators to adopt only the best practices of traditional face-to-face assessment while exploring evaluation tools made available by a digital learning environment in the hopes of arriving at methods that capture the widest set of learner skills and attributes.


Author : Mark Ryan
Publisher : Manning Publications
Release : 2020-12-29
Page : 273
Category : Computers
ISBN 13 : 1617296724
Description :


Deep learning offers the potential to identify complex patterns and relationships hidden in data of all sorts. Deep Learning with Structured Data shows you how to apply powerful deep learning analysis techniques to the kind of structured, tabular data you'll find in the relational databases that real-world businesses depend on. Filled with practical, relevant applications, this book teaches you how deep learning can augment your existing machine learning and business intelligence systems. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub formats from Manning Publications.


Author : John D. Kelleher
Publisher : MIT Press
Release : 2019-09-10
Page : 296
Category : Computers
ISBN 13 : 0262537559
Description :


An accessible introduction to the artificial intelligence technology that enables computer vision, speech recognition, machine translation, and driverless cars. Deep learning is an artificial intelligence technology that enables computer vision, speech recognition in mobile phones, machine translation, AI games, driverless cars, and other applications. When we use consumer products from Google, Microsoft, Facebook, Apple, or Baidu, we are often interacting with a deep learning system. In this volume in the MIT Press Essential Knowledge series, computer scientist John Kelleher offers an accessible and concise but comprehensive introduction to the fundamental technology at the heart of the artificial intelligence revolution. Kelleher explains that deep learning enables data-driven decisions by identifying and extracting patterns from large datasets; its ability to learn from complex data makes deep learning ideally suited to take advantage of the rapid growth in big data and computational power. Kelleher also explains some of the basic concepts in deep learning, presents a history of advances in the field, and discusses the current state of the art. He describes the most important deep learning architectures, including autoencoders, recurrent neural networks, and long short-term networks, as well as such recent developments as Generative Adversarial Networks and capsule networks. He also provides a comprehensive (and comprehensible) introduction to the two fundamental algorithms in deep learning: gradient descent and backpropagation. Finally, Kelleher considers the future of deep learning—major trends, possible developments, and significant challenges.


Author : Gareth Michael James
Daniela Witten
Publisher : Springer Nature
Release : 2021
Page :
Category : Electronic books
ISBN 13 : 1071614185
Description :


An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, deep learning, survival analysis, multiple testing, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra. This Second Edition features new chapters on deep learning, survival analysis, and multiple testing, as well as expanded treatments of naive Bayes, generalized linear models, Bayesian additive regression trees, and matrix completion. R code has been updated throughout to ensure compatibility.


Author : Jeremy Howard
Sylvain Gugger
Publisher : O'Reilly Media
Release : 2020-06-29
Page : 624
Category : Computers
ISBN 13 : 1492045497
Description :


Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala


Author : Wojciech W. Gasparski
David Botham
Publisher : Transaction Publishers
Release : 1998
Page : 221
Category : Philosophy
ISBN 13 : 9781412816373
Description :


Comprises 13 contributions on praxiology, the study of working and doing from the point of view of effectiveness. The three components of praxiology are addressed: analysis of concepts involving purposive actions; critique of modes of action from the viewpoint of efficiency; and normative advisory aspects in recommendations for increasing human efficacy. Representative topics include critical systems heuristics, applications and case studies in learning by action, the relevance of action learning for business ethics, and the case of the Polish environmental movement. Intended for sociologists, philosophers, managers, and researchers of all disciplines. Annotation c. Book News, Inc., Portland, OR (booknews.com)


Author : Gordon Grant
Paul Ramcharan
Publisher : McGraw-Hill Education (UK)
Release : 2010-05-16
Page : 784
Category : Political Science
ISBN 13 : 0335238440
Description :


Annotation "The editors have brought together a range of eminent contributors who present a range of issues throughout the life cycle. The book asserts that it hopes to 'assist readers to anticipate change and discontinuity in people's lives and think about strategies to support them' through the many challenges that they may face in their lives. In my view this book certainly does that and the editors and contributors are to be congratulated on the production of a relevant and contemporary text that I have no hesitation in both endorsing and recommending to all involved in supporting and or caring for people with learning disabilities."Professor Bob Gates, Project Leader - Learning Disabilities Workforce Development, NHS Education South Central, UK"The editors have gathered an authoritative faculty to present and discuss a range of contemporary issues; both practical and ethical. The text is well grounded in the lived experience of people with disability and draws on the evidence-base of contemporary science. Each chapter includes thought provoking exercises. This is a seminal text for students and practitioners, researchers and policy makers."Associate Professor Keith R. McVilly, Deakin University, Australia"I currently own a copy of the first edition and it has proved an invaluable resource time and time again. There is not an essay I complete that does not make reference to the book and I can consistently use it to reflect back on my practice as a student nurse and social worker. Having read several extracts from the new edition it does appear to include very high quality content covering learning disabilities over the lifespan ... if I were to personally recommend any book for budding or current learning disability professionals then this would be it."James Grainger, Student Nurse/Social Worker, Sheffield Hallam University, UK"I like the way it has primary and secondary information from a range of sources. The exercises in the book also get you to think about the situation in question which helps us think about our values and anti-oppressive practice ... This book really does start with the basics and having a learning disability from birth and the effects, to in depth knowledge and literature ... This book would be very helpful to me as it brings in literature policies and models from both a health and social side, which is important for my course and collaborative working."Laura Jean Lowe, Student Nurse, Sheffield Hallam University, UK"It is written with a clearly conveyed in-depth knowledge and in a way that has professional lived experience within the context of the work. The authors have taken into account the emotional, client-centred approach to the modern practitioner's practice ... The book gives a true wealth of good practice scenarios that can only help practitioners be good at what they do and aspire to be."Lee Marshall, Student Nurse, Sheffield Hallam University, UKWith its spread of chapters covering key issues across the life cycle this text has established itself as the foundational primer for those studying the lived experiences of people with learning disabilities and their families, and outcomes achieved through services and support systems.Recognising learning disability as a lifelong disability, this accessible book is structured around the life cycle. The second edition is refreshed and expanded to include seven new chapters, covering:AetiologyBreaking news (about disability) and early interventionTransition to adulthoodThe sexual lives of womenEmploymentPersonalisationPeople with hidden identitiesWith contributions from respected figures from a range of disciplines, the book draws heavily upon multidisciplinary perspectives and is based on the latest research and evidence for practice. The text is informed by medical, social and legal models of learning disability, exploring how "learning disability" is produced, reproduced and understood.Extensive use is made of real-life case studies, designed to bring theory, values, policy and practice to life. Narrative chapters describe, in the words of people with learning disabilities themselves, their lives and aspirations. They helpfully show readers the kinds of roles played by families, advocates and services in supporting people with learning disabilities. New exercises and questions have been added to encourage discussion and reflection on practice.Learning Disabilityis core reading for students entering health and social care professions to work with people with learning disabilities. It is a compelling reference text for practitioners as it squarely addresses the challenges facing people with learning disability, their loved ones and the people supporting them.ContributorsDawn Adams, Kathryn Almack, Dorothy Atkinson, Nigel Beail, Christine Bigby, Alison Brammer, Jacqui Brewster, Hilary Brown, Jennifer Clegg, Lesley Cogher, Helen Combes, Clare Connors, Bronach Crawley, Eric Emerson, Margaret Flynn, Linda Gething, Dan Goodley, Peter Goward, Gordon Grant, Chris Hatton, Sheila Hollins, Jane Hubert, Kelley Johnson, Gwynnyth Llewellyn, Heather McAlister, Michelle McCarthy, Alex McClimens, Roy McConkey, David McConnell, Keith McKinstrie, Fiona Mackenzie, Ghazala Mir, Ada Montgomery, Lesley Montisci, Elizabeth Murphy, Chris Oliver, Richard Parrott, Paul Ramcharan, Malcolm Richardson, Bronwyn Roberts, Philippa Russell, Kirsten Stalker, Martin Stevens, John Taylor, Irene Tuffrey-Wijne, Sally Twist, Jan Walmsley, Kate Woodcock


Author : Peter Cantillon
Diana F. Wood
Publisher : John Wiley & Sons
Release : 2017-09-25
Page : 136
Category : Medical
ISBN 13 : 1118892178
Description :


ABC of Learning and Teaching in Medicine is an invaluable resource for both novice and experienced medical teachers. It emphasises the teacher’s role as a facilitator of learning rather than a transmitter of knowledge, and is designed to be practical and accessible not only to those new to the profession, but also to those who wish to keep abreast of developments in medical education. Fully updated and revised, this new edition continues to provide an accessible account of the most important domains of medical education including educational design, assessment, feedback and evaluation. The succinct chapters contained in this ABC are designed to help new teachers learn to teach and for experienced teachers to become even better than they are. Four new chapters have been added covering topics such as social media; quality assurance of assessments; mindfulness and learner supervision. Written by an expert editorial team with an international selection of authoritative contributors, this edition of ABC of Learning and Teaching in Medicine is an excellent introductory text for doctors and other health professionals starting out in their careers, as well as being an important reference for experienced educators.


Author : Andrew Ravenscroft
Stefanie Lindstaedt
Publisher : Springer
Release : 2012-09-18
Page : 553
Category : Computers
ISBN 13 : 3642332633
Description :


This book constitutes the refereed proceedings of the 7th European Conference on Technology Enhanced Learning, EC-TEL 2012, held in Saarbrücken, Germany, in September 2012. The 26 revised full papers presented were carefully reviewed and selected from 130 submissions. The book also includes 12 short papers, 16 demonstration papers, 11 poster papers, and 1 invited paper. Specifically, the programme and organizing structure was formed through the themes: mobile learning and context; serious and educational games; collaborative learning; organisational and workplace learning; learning analytics and retrieval; personalised and adaptive learning; learning environments; academic learning and context; and, learning facilitation by semantic means.


Author : David Boud
Nicky Solomon
Publisher : McGraw-Hill Education (UK)
Release : 2001-02-16
Page : 256
Category : Education
ISBN 13 : 0335230857
Description :


This book is a radical approach to the notion of higher education. Students undertake study for a degree or diploma primarily in their workplace and their learning opportunities are not contrived for study purposes but arise from normal work. Work-based Learning is the first comprehensive book on this major innovation.


Author : Stephen Billett
Christian Harteis
Publisher : Springer
Release : 2014-07-15
Page : 1383
Category : Education
ISBN 13 : 9401789029
Description :


The International Handbook of Research in Professional and Practice-based Learning discusses what constitutes professionalism, examines the concepts and practices of professional and practice-based learning, including associated research traditions and educational provisions. It also explores professional learning in institutions of higher and vocational education as well the practice settings where professionals work and learn, focusing on both initial and ongoing development and how that learning is assessed. The Handbook features research from expert contributors in education, studies of the professions, and accounts of research methodologies from a range of informing disciplines. It is organized in two parts. The first part sets out conceptions of professionalism at work, how professions, work and learning can be understood, and examines the kinds of institutional practices organized for developing occupational capacities. The second part focuses on procedural issues associated with learning for and through professional practice, and how assessment of professional capacities might progress. The key premise of this Handbook is that during both initial and ongoing professional development, individual learning processes are influenced and shaped through their professional environment and practices. Moreover, in turn, the practice and processes of learning through practice are shaped by their development, all of which are required to be understood through a range of research orientations, methods and findings. This Handbook will appeal to academics working in fields of professional practice, including those who are concerned about developing these capacities in their students. In addition, students and research students will also find this Handbook a key reference resource to the field.


Author : Jin, Zheng
Publisher : IGI Global
Release : 2014-10-31
Page : 337
Category : Psychology
ISBN 13 : 1466666005
Description :


While widely studied, the capacity of the human mind remains largely unexplored. As such, researchers are continually seeking ways to understand the brain, its function, and its impact on human behavior. Exploring Implicit Cognition: Learning, Memory, and Social Cognitive Processes explores research surrounding the ways in which an individual’s unconscious is able to influence and impact that person’s behavior without their awareness. Focusing on topics pertaining to social cognition and the unconscious process, this title is ideal for use by students, researchers, psychologists, and academicians interested in the latest insights into implicit cognition.


Author : Colleen Kawalilak
Janet Groen
Publisher : Canadian Scholars’ Press
Release : 2014
Page : 249
Category : Adult learning
ISBN 13 : 1551306379
Description :


This book provides educators and facilitators with a comprehensive overview of the historical underpinnings and philosophical orientations of adult education and adult learning while attending to the various roles individuals play both within and beyond the formal constraints of the classroom. Positioning learners' and instructors' educational narratives as central to the theories that inform adult education, Pathways of Adult Learning opens up a dialogue among students, educators, community members, scholars, and working professionals about the many possible avenues toward knowledge sharing. Employing a personal, accessible tone, Janet Groen and Colleen Kawalilak take up a relational approach that encourages readers to reflect upon their own experiences as learners within the broadening context of adult education. Conscious of the power imbalances that can emerge in both institutional and professional work and learning environments, this text explores specific teaching and facilitation strategies that effectively generate ideas and accommodate adult learners of varying gender orientations, socio-economic backgrounds, and ethnicities. Through their collaborative analysis of a diverse collection of first-person narratives, provided by both students and scholars working in the field, the authors construct a multi-faceted portrait of the status of adult learning today. Integrating a critical lens to explore how social, cultural, and economic factors influence and shape individual and collective pathways toward lifelong learning, this text is an indispensible guide for anyone studying or facilitating educational programming for adults in diverse work and learning contexts


Author : Matthew Taylor
Karl Tuyls
Publisher : Springer
Release : 2010-02-25
Page : 154
Category : Computers
ISBN 13 : 3642118143
Description :


ThisbookpresentsselectedandrevisedpapersoftheSecondWorkshoponAd- tive and Learning Agents 2009 (ALA-09), held at the AAMAS 2009 conference in Budapest, Hungary, May 12. The goalof ALA is to provide an interdisciplinaryforum for scientists from a variety of ?elds such as computer science, biology, game theory and economics. This year’s edition of ALA was the second after the merger of the former wo- shops ALAMAS and ALAg. In 2008 this joint workshop was organized for the ?rst time under the ?ag of both events. ALAMAS was a yearly returning Eu- pean workshop on adaptive and learning agents and multi-agent systems (held eight times). ALAg was the international workshop on adaptive and learning agents, which was usually held at AAMAS. To increase the strength, visibility and quality of the workshop it was decided to merge both workshops under the ?ag of ALA and to set up a Steering Committee as an organizational backbone. This book contains six papers presented during the workshop, which were carefully selected after an additional review round in the summer of 2009. We therefore wish to explicitly thank the members of the Program Committee for the quality and sincerity of their e?orts and service. Furthermore we would like to thank all the members of the senior Steering Committee for making this workshop possible and supporting it with sound advice. We also thank the AAMAS conference for providing us a platform for holding this event. Finally we also wish to thank all authors who responded to our call-for-papers with interesting contributions.