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Machine Learning for Managers

Machine Learning in Translation

Machine Learning in Translation

Machine Learning in Translation introduces machine learning (ML) theories and technologies that are most relevant to translation processes approaching the topic from a human perspective and emphasizing that ML and ML-driven technologies are tools for humans. Providing an exploration of the common ground between human and machine learning and of the nature of translation that leverages this new dimension this book helps linguists translators and localizers better find their added value in a ML-driven translation environment. Part One explores how humans and machines approach the problem of translation in their own particular ways in terms of word embeddings chunking of larger meaning units and prediction in translation based upon the broader context. Part Two introduces key tasks including machine translation translation quality assessment and quality estimation and other Natural Language Processing (NLP) tasks in translation. Part Three focuses on the role of data in both human and machine learning processes. It proposes that a translator’s unique value lies in the capability to create manage and leverage language data in different ML tasks in the translation process. It outlines new knowledge and skills that need to be incorporated into traditional translation education in the machine learning era. The book concludes with a discussion of human-centered machine learning in translation stressing the need to empower translators with ML knowledge through communication with ML users developers and programmers and with opportunities for continuous learning. This accessible guide is designed for current and future users of ML technologies in localization workflows including students on courses in translation and localization language technology and related areas. It supports the professional development of translation practitioners so that they can fully utilize ML technologies and design their own human-centered ML-driven translation workflows and NLP tasks.

GBP 34.99
1

Hands-On Archaeology Authentic Learning Experiences That Engage Students in STEM (Grades 4-5)

Machine Learning and Music Generation

A First Course in Machine Learning

A First Course in Machine Learning

A First Course in Machine Learning by Simon Rogers and Mark Girolami is the best introductory book for ML currently available. It combines rigor and precision with accessibility starts from a detailed explanation of the basic foundations of Bayesian analysis in the simplest of settings and goes all the way to the frontiers of the subject such as infinite mixture models GPs and MCMC. —Devdatt Dubhashi Professor Department of Computer Science and Engineering Chalmers University Sweden This textbook manages to be easier to read than other comparable books in the subject while retaining all the rigorous treatment needed. The new chapters put it at the forefront of the field by covering topics that have become mainstream in machine learning over the last decade. —Daniel Barbara George Mason University Fairfax Virginia USA The new edition of A First Course in Machine Learning by Rogers and Girolami is an excellent introduction to the use of statistical methods in machine learning. The book introduces concepts such as mathematical modeling inference and prediction providing ‘just in time’ the essential background on linear algebra calculus and probability theory that the reader needs to understand these concepts. —Daniel Ortiz-Arroyo Associate Professor Aalborg University Esbjerg Denmark I was impressed by how closely the material aligns with the needs of an introductory course on machine learning which is its greatest strength…Overall this is a pragmatic and helpful book which is well-aligned to the needs of an introductory course and one that I will be looking at for my own students in coming months. —David Clifton University of Oxford UK The first edition of this book was already an excellent introductory text on machine learning for an advanced undergraduate or taught masters level course or indeed for anybody who wants to learn about an interesting and important field of computer science. The additional chapters of advanced material on Gaussian process MCMC and mixture modeling provide an ideal basis for practical projects without disturbing the very clear and readable exposition of the basics contained in the first part of the book. —Gavin Cawley Senior Lecturer School of Computing Sciences University of East Anglia UK This book could be used for junior/senior undergraduate students or first-year graduate students as well as individuals who want to explore the field of machine learning…The book introduces not only the concepts but the underlying ideas on algorithm implementation from a critical thinking perspective. —Guangzhi Qu Oakland University Rochester Michigan USA

GBP 39.99
1

Implicit Learning 50 Years On

Hands-On Literacy Grade 5 Authentic Learning Experiences That Engage Students in Creative and Critical Thinking

Machine Learning Architecture in the age of Artificial Intelligence

Inquiry-Based Literature Instruction in the 6–12 Classroom A Hands-on Guide for Deeper Learning

Learning in Organizations An Evidence-Based Approach

Social Presence in Online Learning Multiple Perspectives on Practice and Research

Social Presence in Online Learning Multiple Perspectives on Practice and Research

Published in Association with 2020 AECT Division of Distance Learning Book AwardSocial presence continues to emerge as a key factor for successful online and blended learning experiences. It is commonly described as the degree to which online participants feel connected to one another. Understanding social presence—with its critical connections to community-building retention and learning outcomes—allows faculty and instructional designers to better support and engage students. This volume Social Presence in Online Learning addresses the evolution of social presence with three distinct perspectives outlines the relevant research and focuses on practical strategies that can immediately impact the teaching and learning experience. These strategies include creating connections to build community applying content to authentic situations integrating a careful mix of tools and media leveraging reflective and interactive opportunities providing early and continuous feedback designing with assessment in mind and encouraging change in small increments. Because student satisfaction and motivation plays a key role in retention rates and because increased social presence often leads to enriched learning experiences it is advantageous to mindfully integrate social presence into learning environments. Social Presence in Online Learning brings together eminent scholars in the field to distinguish among three different perspectives of social presence and to address how these viewpoints immediately inform practice. This important volume: • Provides an overview of the evolution of social presence key findings from social presence research and practical strategies that can improve the online and blended learning experience• Differentiates three distinct perspectives on social presence and explains the ideas and models that inform these perspectives• Explores specific ways in which social presence relates to course satisfaction retention and outcomes• Offers practical implications and ready-to-use techniques that are applicable to multiple disciplines• Introduces current research on social presence by prominent researchers in the field with direct inferences to the practice of online and blended learning • Looks at future directions for social presenceSocial Presence in Online Learning is appropriate for practitioners researchers and academics involved in any level of online learning program design course design instruction support and leadership as well as for graduate students studying educational technology technology-enhanced learning and online and blended learning. It brings together multiple perspectives on social presence from the most influential scholars in the field to help shape the future of online and blended learning. | Social Presence in Online Learning Multiple Perspectives on Practice and Research

GBP 32.99
1

Learning on Location Place-Based Approaches for Diverse Learners in Higher Education

GBP 31.99
1

International Perspectives on Tele-Education and Virtual Learning Environments

Teacher Learning in Changing Contexts Perspectives from the Learning Sciences

Teacher Learning in Changing Contexts Perspectives from the Learning Sciences

New to the Routledge Advances in Learning Sciences series this book highlights diverse approaches taken by researchers in the Learning Sciences to support teacher learning. It features international perspectives from world class researchers that exemplify new lenses on the work of teaching encompassing new objects of learning methods and tools; new ways of working with researchers and peers; and new efforts to work with the systems in which teachers are embedded. Together the chapters in this volume reflect a new frontier of research on teacher learning that leverages diversity in the content contexts objects of inquiry and tools for supporting shifts in instructional practice. Divided into three sections chapters question: What new pedagogies and knowledge do teachers need to facilitate student learning in the 21st century? How do learning sciences’ tools strategies and experiences provide opportunities for them to learn these? What role do teachers play as co-designers of educational innovations? What unique affordances does co-design afford for teacher learning? What do teachers learn through engaging in co-design? How do teachers work and learn as part of interdisciplinary teams within educational systems? What might it look like to design for teacher learning in these broader organizational systems? Uniquely highlighting how cycles of reflection and co-design can serve as important mechanisms to support teacher learning this invaluable book lays the groundwork for sustained teacher learning and instructional improvement. | Teacher Learning in Changing Contexts Perspectives from the Learning Sciences

GBP 35.99
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Visible Learning Insights

Unpacking your Learning Targets Aligning Student Learning to Standards