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An introduction to machine learning that includes the fundamental techniques, methods, and applications Machine Learning: a Concise Introduction offers a comprehensive introduction to the core concept

Machine learning is an interdisciplinary field of science and engineering that studies mathematical theories and practical applications of systems that learn. This book introduces theories, methods and applications of density ratio estimation, which is a newly emerging paradigm in the machine learning community. Various machine learning problems such as non-stationarity adaptation, outlier detection, dimensionality reduction, independent component analysis, clustering, classification and conditional density estimation can be systematically solved via the estimation of probability density ratios. The authors offer a comprehensive introduction of various density ratio estimators including methods via density estimation, moment matching, probabilistic classification, density fitting and density ratio fitting, as well as describing how these can be applied to machine learning. The book provides mathematical theories for density ratio estimation including parametric and non-parametric conve

This integrated collection of perspectives on the spaces of teaching and learning uses ‘learning space’ to place educational practice in context. It considers the complex relationships involved in the

Machine learning can be a difficult subject if you’re not familiar with the basics. With this book, you'll get a solid foundation of introductory principles used in machine learning with the sta

Learning Architectures in Higher Education restores criticality and rigour to the study of communities of practice as a means of understanding learning, acknowledging that this is one of the most

Inquiry, laboratory, project-based learning, discovery learning—which science instructional approach is most effective? In Visible Learning for Science, the authors reveal that it’s not wh

Drawing from research in developmental and educational psychology, cognitive science, and the learning sciences, Five Teaching and Learning Myths—Debunked addresses some of the most commonly misunders

Drawing from research in developmental and educational psychology, cognitive science, and the learning sciences, Five Teaching and Learning Myths—Debunked addresses some of the most commonly misunders

Practical, up-to-date guidance on identifying Specific Learning Disability Essentials of Specific Learning Disability Identification provides accessible, authoritative guidance on specific learning di

Designing for Learning in a Networked World provides answers to the following questions: what skills are required for living in a networked world; how can educators design for learning these skills an

Deep Learning is now ubiquitous with applied machine learning. All of the technology giants (e.g. Google, Microsoft, Apple, etc.) are focusing on deep learning based techniques for data analytics and

"This volume brings together design thinking, critical social theory, and learning sciences to describe promising learning innovations that foster rights, dignity, and social justice for youth. Each o

Originally published in 1989, this title presents a view of adaptive behaviour which integrates both evolutionary and psychological perspectives on learning. The study of learning, and in particular c

Learn how to solve challenging machine learning problems with Tensorflow, Google’s revolutionary new system for deep learning. If you have some background with basic linear algebra and calculus,

Investigating children’s learning through dance and drawing telling, Dance-Play and Drawing as Semiotic Tools for Young Children’s Learning provides a unique insight into how these activities can help

Social anthropologist Jean Lave and computer scientist Etienne Wenger’s seminal Situated Learning helped change the fields of cognitive science and pedagogy by approaching learning from a novel angle.

Although the difficulties many students encounter when learning chemistry have been known and explored for decades, there is no consensus on how best to assist and assess their learning. Over the past

This innovative book focuses on the relationships among self-regulated language learning strategies, students' individual characteristics, and the diverse contexts in which learning occurs. It present

Motivation, Learning, and Technology is a fresh, thorough, and practical introduction to motivational research, theories, and applications for learning and instruction. Written for both instructional

Master the essential skills needed to recognize and solve complex problems with machine learning and deep learning. Using real-world examples that leverage the popular Python machine learning ecosyste

Informal Learning at Work reflects the growing interest in changing the way the workplace encourages and enhances learning and professional development. Due to societal, economic, and technological de

Informal Learning at Work reflects the growing interest in changing the way the workplace encourages and enhances learning and professional development. Due to societal, economic, and technological de

This book develops a machine-learning framework for predicting economic growth. It can also be considered as a primer for using machine learning (also known as data mining or data analytics) to answer

本書由淺入深，系統、詳盡地介紹了HTML5、CSS3和JavaScript相關技術及其在Web前端及移動應用開發領域的應用。書中提供了大量的代碼示例，從基本原理到實戰應用，幾乎涉及了Web前端及移動應用開發的絕大部分內容。 本書分為四篇，共17章。第一篇為HTML和HTML5技術，涵蓋的內容包括HTML網頁基礎、頁面元素、文字與排版、網頁圖像、超鏈接、表格與表單和HTML5新特性等方面的內容；第二

本書主要內容包括：JSP概述、Java語言基礎、JavaScript編程基礎、JSP頁面元素及內置對象、JSP與Servlet等。

Written by leading researchers, this complete introduction brings together all the theory and tools needed for building robust machine learning in adversarial environments. Discover how machine learning systems can adapt when an adversary actively poisons data to manipulate statistical inference, learn the latest practical techniques for investigating system security and performing robust data analysis, and gain insight into new approaches for designing effective countermeasures against the latest wave of cyber-attacks. Privacy-preserving mechanisms and the near-optimal evasion of classifiers are discussed in detail, and in-depth case studies on email spam and network security highlight successful attacks on traditional machine learning algorithms. Providing a thorough overview of the current state of the art in the field, and possible future directions, this groundbreaking work is essential reading for researchers, practitioners and students in computer security and machine learning,

Design high-impact professional learning programs with results-based evaluationsYou want to make sure that the time, effort, and resources you are investing in your professional learning programs is t

Mobile Learning and Higher Education provides case studies of mobile learning in higher education settings to showcase how devices can transform learning at the undergraduate and graduate levels. With

Master reinforcement learning, a popular area of machine learning, starting with the basics: discover how agents and the environment evolve and then gain a clear picture of how they are inter-related.

In Organizational Learning and Performance: The Science and Practice of Building a Learning Culture, Ryan Smerek combines organizational examples with insights from research, to provide readers with a

Cultivating a Culture of Learning illustrates practice from a variety of teacher education programs. Authors share their first-hand experience of cultivating a culture of learning as teacher educators

Cultivating a Culture of Learning illustrates practice from a variety of teacher education programs. Authors share their first-hand experience of cultivating a culture of learning as teacher educators

According to Bayesian epistemology, rational learning from experience is consistent learning, that is learning should incorporate new information consistently into one's old system of beliefs. Simon M. Huttegger argues that this core idea can be transferred to situations where the learner's informational inputs are much more limited than Bayesianism assumes, thereby significantly expanding the reach of a Bayesian type of epistemology. What results from this is a unified account of probabilistic learning in the tradition of Richard Jeffrey's 'radical probabilism'. Along the way, Huttegger addresses a number of debates in epistemology and the philosophy of science, including the status of prior probabilities, whether Bayes' rule is the only legitimate form of learning from experience, and whether rational agents can have sustained disagreements. His book will be of interest to students and scholars of epistemology, of game and decision theory, and of cognitive, economic, and computer sci

An Introduction to Foreign Language Learning and Teaching provides an engaging, student-friendly guide to the field of foreign language learning and teaching. Aimed at students with no background in t

Around the world, children embark on learning to read in their home language or writing system. But does their specific language, and how it is written, make a difference to how they learn? How is learning to read English similar to or different from learning in other languages? Is reading alphabetic writing a different challenge from reading syllabic or logographic writing? Learning to Read across Languages and Writing Systems examines these questions across seventeen languages representing the world's different major writing systems. Each chapter highlights the key features of a specific language, exploring research on learning to read, spell, and comprehend it, and on implications for education. The editors' introduction describes the global spread of reading and provides a theoretical framework, including operating principles for learning to read. The editors' final chapter draws conclusions about cross-linguistic universal trends, and the challenges posed by specific languages and

An Introduction to Foreign Language Learning and Teaching provides an engaging, student-friendly guide to the field of foreign language learning and teaching. Aimed at students with no background in t

Learning and Memory provides a broad survey of topics including the major behaviorism theories of learning, modern cognitive theories of memory, social learning theories, the roles of emotion and moti

This book explores learning in the early years and emphasises the importance of learning in social contexts, through the senses and within close relationships. It moves away from the focus on ‘learnin

This book explores learning in the early years and emphasises the importance of learning in social contexts, through the senses and within close relationships. It moves away from the focus on ‘learnin

Museum Learning employs a ‘learning’ lens to highlight the insights as well as practical implications and applications theoretical approaches can offer museum studies students, practitioners and resea