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This book will help readers understand fundamental and advanced statistical models and deep learning models for robust speaker recognition and domain adaptation. This useful toolkit enables readers to apply machine learning techniques to address practical issues, such as robustness under adverse acoustic environments and domain mismatch, when deploying speaker recognition systems. Presenting state-of-the-art machine learning techniques for speaker recognition and featuring a range of probabilistic models, learning algorithms, case studies, and new trends and directions for speaker recognition based on modern machine learning and deep learning, this is the perfect resource for graduates, researchers, practitioners and engineers in electrical engineering, computer science and applied mathematics.

運用JavaScript工具堆疊「Ethan太了不起了，因為他不會預設讀者已經知道什麼，或是不知道什麼。很開心看到他不僅成功地介紹NodeJS/Express生態系統，也花一些時間幫初學者介紹web開發概念，例如持久保存、中介函式，以及Git。」—Alejandra Olvera-NovackAWS Developer Relations使用Node/JavaScript開發堆疊的主要工具Expr

本書共分13章, 第1章主要講述Web前端開發技術基本概念, 第2-6章介紹了HTML基礎標簽及相關屬性, 第7-8章介紹CSS的語法及屬性, 第9章主要介紹當前流行的DIV佈局技術, 第10章介紹表單技術, 第11章介紹HTML5及CSS3的新特性, 第12章介紹JavaScript基礎, 第13章介紹jQuery與Ajax應用。本書配有課程教學大綱、教案、課件PPT、微課視頻、案例源代碼及素材

100 Ideas for Primary Teachers: Outdoor Learning is packed with inspiring ideas to generate enthusiasm and engage pupils in learning through positive outdoor experiences. These can then be used as a s

《HTML5+CSS3+JavaScript從入門到精通（微視頻精編版套裝共2本）/軟件開發微視頻講堂》內容淺顯易懂，實例豐富，詳細介紹了HTML5+CSS3+JavaScript開發需要掌握的各類實戰知識。 全書分為兩冊：核心技術分冊和強化訓練分冊。核心技術分冊共17章，包括HTML，基礎、文本、圖像和超鏈接、CSS3概述、CSS3高級應用、表格與標籤、列表、表單、多媒體、HTML5新特性

Online learning is ubiquitous for millions of students worldwide, yet our understanding of student experiences in online learning settings is limited. The geographic distance that separates faculty fr

A simple user-friendly book which helps complete beginners of all ages get started using the web languages, HTML, CSS and JavaScript. After finishing this book, readers will have built their own

Implementing evidence-based and innovative teaching practices can feel like juggling: If you have standards-based learning in one hand and social-emotional learning in the other, what do you do with c

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

Transfer learning deals with how systems can quickly adapt themselves to new situations, tasks and environments. It gives machine learning systems the ability to leverage auxiliary data and models to help solve target problems when there is only a small amount of data available. This makes such systems more reliable and robust, keeping the machine learning model faced with unforeseeable changes from deviating too much from expected performance. At an enterprise level, transfer learning allows knowledge to be reused so experience gained once can be repeatedly applied to the real world. For example, a pre-trained model that takes account of user privacy can be downloaded and adapted at the edge of a computer network. This self-contained, comprehensive reference text describes the standard algorithms and demonstrates how these are used in different transfer learning paradigms. It offers a solid grounding for newcomers as well as new insights for seasoned researchers and developers.

Blended learning offers educators the opportunity to reimagine teaching and learning. It allows teachers to partner with their students to assess, track, and reflect on learning. This partnership give

本書全面、系統地介紹網頁設計與製作所涉及的各方面的內容和技巧，涵蓋網頁設計流程和各種Web前端技術：HTML、CSS、JavaScript和HTML5。每章都配置大量的實用案例，圖文並茂，效果直觀。 本書分5篇，共26章。第1篇主要介紹HTML相關概念、HTML文檔結構、網頁設計流程、網頁製作方法，以及各種常用的HTML標記的用法等內容；第2篇詳細介紹CSS基礎知識、CSS的定義、CSS常用屬性、

The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every cha

Much has been written about the escalating intolerance of worldviews other than one's own. Reasoned arguments based on facts and data seem to have little impact in our increasingly post-truth culture dominated by social media, fake news, tribalism, and identity politics. Recent advances in the study of human cognition, however, offer insights on how to counter these troubling social trends. In this book, psychologist Jon F. Wergin calls upon recent research in learning theory, social psychology, politics, and the arts to show how a deep learning mindset can be developed in both oneself and others. Deep learning is an acceptance that our understanding of the world around us is only temporary and is subject to constant scrutiny. Someone who is committed to learning deeply does not simply react to experiences, but engages fully with that experience, knowing that the inevitable disquietude is what leads to efficacy in the world.

Much has been written about the escalating intolerance of worldviews other than one's own. Reasoned arguments based on facts and data seem to have little impact in our increasingly post-truth culture dominated by social media, fake news, tribalism, and identity politics. Recent advances in the study of human cognition, however, offer insights on how to counter these troubling social trends. In this book, psychologist Jon F. Wergin calls upon recent research in learning theory, social psychology, politics, and the arts to show how a deep learning mindset can be developed in both oneself and others. Deep learning is an acceptance that our understanding of the world around us is only temporary and is subject to constant scrutiny. Someone who is committed to learning deeply does not simply react to experiences, but engages fully with that experience, knowing that the inevitable disquietude is what leads to efficacy in the world.

The fundamental mathematical tools needed to understand machine learning include linear algebra, analytic geometry, matrix decompositions, vector calculus, optimization, probability and statistics. These topics are traditionally taught in disparate courses, making it hard for data science or computer science students, or professionals, to efficiently learn the mathematics. This self-contained textbook bridges the gap between mathematical and machine learning texts, introducing the mathematical concepts with a minimum of prerequisites. It uses these concepts to derive four central machine learning methods: linear regression, principal component analysis, Gaussian mixture models and support vector machines. For students and others with a mathematical background, these derivations provide a starting point to machine learning texts. For those learning the mathematics for the first time, the methods help build intuition and practical experience with applying mathematical concepts. Every cha

本書主要講解web前端開發中用到的HTML、CSS和JavaScript技術，與同類書籍區別的是，本書不是分開講解HTML、CSS和JavaScript技術，而是以網頁中的內容類別進行劃分版塊，每個板塊綜合講解該內容類別需用到的HTML、CSS、JavaScript技術，並配有實用案例進行分析演示，旨在讓一個零基礎的初學者能夠快速掌握系統的知識並能夠快速上手開發實際項目。本書可作為高等院校或大、中

無論是網頁的前端還是移動App的前端都離不開HTML+CSS+JavaScript，而學習這3門技術的基本要求就是多動手操作和多練習頁面實例。本書通過實例的方式講解前端基礎，旨在幫助讀者從一位網頁開發初學者躍升為真正的前端開發人員。本書分為30章，內容包括網頁前端開發和移動端開發的一些必備知識，涵蓋常用的表單、圖片、按鈕、鏈接、背景、動畫、佈局、3D、移動開發、觸屏開發等技術，涉及HTML、HTM

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

This book presents the theory of output-driven maps and provides a fresh perspective on the extent to which phonologies can be characterized in terms of restrictions on outputs. Closely related to traditional conceptions of process opacity, but differing in notable ways, the theory of output-driven maps applies equally to SPE-style ordered rules, Optimality Theory, and other phonological theories. It permits a formally rigorous analysis of the issues in Optimality Theory that is not possible with traditional process opacity. Also presented is a theory of phonological learning. Building on prior work on learning in Optimality Theory, the learning theory exploits the formal structure of output-driven maps to achieve learning that is far more computationally efficient than comparable prior approaches. In this book Bruce Tesar, one of the founders of the study of learnability in Optimality Theory, presents fresh perspectives in an accessible way for graduate students and academic researche

本書系統地講述了HTML、CSS和JavaScript等Web前端開發技術，範圍覆蓋HTML5與CSS3的新技術與典型應用，實現網站開發技術從傳統的HTML+CSS向HTML5+CSS3過渡。本書內容主要分為四部分。第一部分包括第1章和第2章，介紹HTML中廣泛使用的標記和屬性，也包括HTML5中一些新增的標記和屬性。第二部分包括第3章、第4章，介紹了CSS的概念、應用，也包括CSS3的盒模型、C

Learning to See = Seeing to Learn: Vision, Learning & Behavior by Dr. Patrick Quaid et al, will unlock the connection between eyesight, education, and behaviors in children. How can you have 20/20

An essential tool for new teachers and trainees who want to use learning theories to develop their practice. The text explores key learning theories in a pragmatic way and encourages focused reflectio

Learning, innovation and adaptation are not concepts that we necessarily associate with the British army of the First World War. Yet the need to learn from mistakes, to exploit new opportunities and to adapt to complex situations are enduring and timeless. This revealing work is the first institutional examination of the army's process for learning during the First World War. Drawing on organisational learning and management theories, Aimée Fox critiques existing approaches to military learning in wartime. Focused around a series of case studies, the book ranges across multiple operational theatres and positions the army within a broader context in terms of its relationships with allies and civilians to reveal that learning was more complex and thoroughgoing than initially thought. It grapples with the army's failings and shortcomings, explores its successes and acknowledges the inherent difficulties of learning in a desperate and lethally competitive environment.

An accessible introduction to the artificial intelligence technology that enables computer vision, speech recognition, machine translation, and driverless cars.Deep learning is an artificial intellige

本書展示使用JavaScript構建響應周圍世界的機器人的方法。書中詳細介紹使用帶有Arduino、樹莓派和BeagleBone的開源Johnny-Five機器人庫，逐步構建和編程能夠漫遊、游泳、打字、散步、跳舞、發送提醒、製作音樂、表達情感等的機器人的方法。書中詳細說明了項目所需的材料，找到材料的地點以及購買材料的估計成本，並且在計劃和排除項目故障的過程中會提供大量幫助，這樣你可以輕鬆地構建本書

Variational Bayesian learning is one of the most popular methods in machine learning. Designed for researchers and graduate students in machine learning, this book summarizes recent developments in the non-asymptotic and asymptotic theory of variational Bayesian learning and suggests how this theory can be applied in practice. The authors begin by developing a basic framework with a focus on conjugacy, which enables the reader to derive tractable algorithms. Next, it summarizes non-asymptotic theory, which, although limited in application to bilinear models, precisely describes the behavior of the variational Bayesian solution and reveals its sparsity inducing mechanism. Finally, the text summarizes asymptotic theory, which reveals phase transition phenomena depending on the prior setting, thus providing suggestions on how to set hyperparameters for particular purposes. Detailed derivations allow readers to follow along without prior knowledge of the mathematical techniques specific to

In order to design and deliver effective learning and development initiatives, it is essential to understand how our brains process and retain information. Neuroscience for Learning and Development in

Put the power of AWS Cloud machine learning services to work in your business and commercial applications! Machine Learning in the AWS Cloud introduces readers to the machine learning (ML) capabiliti

Assessing Deeper Learning explores how performance assessment advances deeper learning—the skills students need for 21st century success. The book examines different aspects of performance asses

Assessing Deeper Learning explores how performance assessment advances deeper learning—the skills students need for 21st century success. The book examines different aspects of performance asses

Professional Learning Communities charts a streamlined process for creating a PLC. The highest mission of a professional learning community is academic achievement. During Dr. Culp's forty-plus years

本書以“採用網頁新標準技術、突破傳統知識體系結構、基於工作能力培養、置身真實工作情境”為標準，通過任務驅動的教學方式講解HTML5、CSS3、JavaScript等Web前端開發技術。本書包含“8個知識單元、18個項目任務、36個實戰案例、18個課後實訓”，每個項目任務又以“知識準備→實戰演練→強化訓練→課後實訓”為主線，介紹了Web基礎知識、HTML5語言基礎、HTML5新增標簽及屬性、CSS3

本書是“十二五”職業教育國家規劃教材修訂版。 本書由點到面以能力遞進的“單元基礎知識+單元實例”，系統講述了運用HTML5 + CSS3 + JavaScript開發Web應用的必備知識，並選取以能力成長為目標的典型案例進行強化訓練，包括：創建HTML5頁面、應用CSS和CSS3樣式、開發調試工具、JavaScript與DOM、CSS和JavaScript應用、Canvas應用等。讀者通過學習能

Written for teachers—and everyone interested in teaching and learning—Learning Deepens helps classrooms flourish by fostering students’ intrinsic motivation. By interleaving psycholo

Learning by Expanding challenges traditional theories that consider learning to be a process of acquisition and reorganization of cognitive structures within the closed boundaries of specific tasks or problems. Yrjö Engeström argues that this type of learning increasingly fails to meet the challenges of complex social change and fails to create novel artifacts and ways of life. In response, he presents an innovative theory of expansive learning activity, offering a foundation for understanding and designing learning as a transformation of human activities and organizations. The second edition of this seminal text features a substantive new introduction that illustrates the development and implementation of Engeström's theory since its inception.

"Why are you learning Zulu?" When Mark Sanders began studying the language, he was often asked this question. In Learning Zulu, Sanders places his own endeavors within a wider context to uncover how,

Written by world-renowned social anthropologist, Jean Lave, with an afterword by Brazilian anthropologist Ana Maria R. Gomes, this book weaves together ethnographic accounts of work and learning, apprenticeship and everyday life, through a critical theory of practice. Each chapter explores in different ways the proposition that learning is a collective, transformative process of change in the historically political complex relations of everyday life. At the same time, the book demonstrates the changing character of Lave's own research practice over two decades. Lave addresses work practices and everyday life and discusses the problem of context and decontextualization. Analyzing two decades of ethnographic studies of craft apprenticeship, she explores teaching as learning and examines the reciprocal effects of theories of everyday life and learning.

Written by world-renowned social anthropologist, Jean Lave, with an afterword by Brazilian anthropologist Ana Maria R. Gomes, this book weaves together ethnographic accounts of work and learning, apprenticeship and everyday life, through a critical theory of practice. Each chapter explores in different ways the proposition that learning is a collective, transformative process of change in the historically political complex relations of everyday life. At the same time, the book demonstrates the changing character of Lave's own research practice over two decades. Lave addresses work practices and everyday life and discusses the problem of context and decontextualization. Analyzing two decades of ethnographic studies of craft apprenticeship, she explores teaching as learning and examines the reciprocal effects of theories of everyday life and learning.

As the complexity of 21st century disciplines has increased it has become necessary to rethink the design and delivery of learning to more effectively serve the diverse needs and learning styles of st