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Author: Ian Goodfellow Publisher: MIT Press ISBN: 0262337371 Category : Computers Languages : en Pages : 801
Book 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: Ian Goodfellow Publisher: MIT Press ISBN: 0262337371 Category : Computers Languages : en Pages : 801
Book 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: National Institute on Out-of-School Time (U.S.) Publisher: Ingram ISBN: Category : Education Languages : en Pages : 188
Book Description
Get all the tools your after-school program needs for a well-balanced program. This resource provides an overview of learning and child development; offers tips and tools for selecting, planning, developing and evaluating after-school activities; and demonstrates how to link these activities to sample learning and quality standards. The book also introduces the reader to curriculum resources focusing on seven key learning areas believed to be central to comprehensive, high-quality, after-school programs.
Author: Julie Stern Publisher: Corwin Press ISBN: 1071835874 Category : Education Languages : en Pages : 333
Book Description
"It is a pleasure to have a full length treatise on this most important topic, and may this focus on transfer become much more debated, taught, and valued in our schools." - John Hattie Teach students to use their learning to unlock new situations. How do you prepare your students for a future that you can’t see? And how do you do it without exhausting yourself? Teachers need a framework that allows them to keep pace with our rapidly changing world without having to overhaul everything they do. Learning That Transfers empowers teachers and curriculum designers alike to harness the critical concepts of traditional disciplines while building students’ capacity to navigate, interpret, and transfer their learning to solve novel and complex modern problems. Using a backwards design approach, this hands-on guide walks teachers step-by-step through the process of identifying curricular goals, establishing assessment targets, and planning curriculum and instruction that facilitates the transfer of learning to new and challenging situations. Key features include Thinking prompts to spur reflection and inform curricular planning and design. Next-day strategies that offer tips for practical, immediate action in the classroom. Design steps that outline critical moments in creating curriculum for learning that transfers. Links to case studies, discipline-specific examples, and podcast interviews with educators. A companion website that hosts templates, planning guides, and flexible options for adapting current curriculum documents. Using a framework that combines standards and the best available research on how we learn, design curriculum and instruction that prepares your students to meet the challenges of an uncertain future, while addressing the unique needs of your school community.
Author: Richard S. Sutton Publisher: MIT Press ISBN: 0262352702 Category : Computers Languages : en Pages : 549
Book 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: Jennifer Robbins Publisher: "O'Reilly Media, Inc." ISBN: 1491960159 Category : Languages : en Pages : 1096
Book Description
Do you want to build web pages but have no prior experience? This friendly guide is the perfect place to start. You’ll begin at square one, learning how the web and web pages work, and then steadily build from there. By the end of the book, you’ll have the skills to create a simple site with multicolumn pages that adapt for mobile devices. Each chapter provides exercises to help you learn various techniques and short quizzes to make sure you understand key concepts. This thoroughly revised edition is ideal for students and professionals of all backgrounds and skill levels. It is simple and clear enough for beginners, yet thorough enough to be a useful reference for experienced developers keeping their skills up to date. Build HTML pages with text, links, images, tables, and forms Use style sheets (CSS) for colors, backgrounds, formatting text, page layout, and even simple animation effects Learn how JavaScript works and why the language is so important in web design Create and optimize web images so they’ll download as quickly as possible NEW! Use CSS Flexbox and Grid for sophisticated and flexible page layout NEW! Learn the ins and outs of Responsive Web Design to make web pages look great on all devices NEW! Become familiar with the command line, Git, and other tools in the modern web developer’s toolkit NEW! Get to know the super-powers of SVG graphics
Author: Leslie Haley Wasserman Publisher: Springer Science & Business Media ISBN: 9400766718 Category : Education Languages : en Pages : 226
Book Description
Information from neuroscience is growing and being properly used, and misused wich makes it imperative that educators receive accurate and practical information. This book provides the accurate and practical information educators (pre-service and in-service) and caregivers serving children birth through age 8 need to know. This volume takes a practical and cautionary stance. It reminds educators to consider the ethical implications of neuroscience when it is applied to education, reviews current findings from neuroscience and reveals the dangers of oversimplification and inappropriate extensions of neuroscience into curricula. It brings together a group of authors with varied expertise writing on an array of inter-related educational topics that will help educators use neuroscience to understand and address the cognitive, emotional, social, and behavioral needs of all young children, including those with exceptionalities. They believe neuroscience can be insightful and useful to educators if applied ethically and with care. The book offers strategies educators and caregivers can use to affect children today and the adults they can become.
Author: Barbara Oakley, PhD Publisher: Penguin ISBN: 052550446X Category : Juvenile Nonfiction Languages : en Pages : 258
Book Description
A surprisingly simple way for students to master any subject--based on one of the world's most popular online courses and the bestselling book A Mind for Numbers A Mind for Numbers and its wildly popular online companion course "Learning How to Learn" have empowered more than two million learners of all ages from around the world to master subjects that they once struggled with. Fans often wish they'd discovered these learning strategies earlier and ask how they can help their kids master these skills as well. Now in this new book for kids and teens, the authors reveal how to make the most of time spent studying. We all have the tools to learn what might not seem to come naturally to us at first--the secret is to understand how the brain works so we can unlock its power. This book explains: Why sometimes letting your mind wander is an important part of the learning process How to avoid "rut think" in order to think outside the box Why having a poor memory can be a good thing The value of metaphors in developing understanding A simple, yet powerful, way to stop procrastinating Filled with illustrations, application questions, and exercises, this book makes learning easy and fun.
Author: Grant P. Wiggins Publisher: ASCD ISBN: 1416600353 Category : Education Languages : en Pages : 383
Book Description
What is understanding and how does it differ from knowledge? How can we determine the big ideas worth understanding? Why is understanding an important teaching goal, and how do we know when students have attained it? How can we create a rigorous and engaging curriculum that focuses on understanding and leads to improved student performance in today's high-stakes, standards-based environment? Authors Grant Wiggins and Jay McTighe answer these and many other questions in this second edition of Understanding by Design. Drawing on feedback from thousands of educators around the world who have used the UbD framework since its introduction in 1998, the authors have greatly revised and expanded their original work to guide educators across the K-16 spectrum in the design of curriculum, assessment, and instruction. With an improved UbD Template at its core, the book explains the rationale of backward design and explores in greater depth the meaning of such key ideas as essential questions and transfer tasks. Readers will learn why the familiar coverage- and activity-based approaches to curriculum design fall short, and how a focus on the six facets of understanding can enrich student learning. With an expanded array of practical strategies, tools, and examples from all subject areas, the book demonstrates how the research-based principles of Understanding by Design apply to district frameworks as well as to individual units of curriculum. Combining provocative ideas, thoughtful analysis, and tested approaches, this new edition of Understanding by Design offers teacher-designers a clear path to the creation of curriculum that ensures better learning and a more stimulating experience for students and teachers alike.
Author: Johannes Fürnkranz Publisher: Springer Science & Business Media ISBN: 3642141250 Category : Computers Languages : en Pages : 457
Book Description
The topic of preferences is a new branch of machine learning and data mining, and it has attracted considerable attention in artificial intelligence research in previous years. It involves learning from observations that reveal information about the preferences of an individual or a class of individuals. Representing and processing knowledge in terms of preferences is appealing as it allows one to specify desires in a declarative way, to combine qualitative and quantitative modes of reasoning, and to deal with inconsistencies and exceptions in a flexible manner. And, generalizing beyond training data, models thus learned may be used for preference prediction. This is the first book dedicated to this topic, and the treatment is comprehensive. The editors first offer a thorough introduction, including a systematic categorization according to learning task and learning technique, along with a unified notation. The first half of the book is organized into parts on label ranking, instance ranking, and object ranking; while the second half is organized into parts on applications of preference learning in multiattribute domains, information retrieval, and recommender systems. The book will be of interest to researchers and practitioners in artificial intelligence, in particular machine learning and data mining, and in fields such as multicriteria decision-making and operations research.
Author: Ian Goodfellow
Author: Ian Goodfellow
Author: National Institute on Out-of-School Time (U.S.)
Author: Julie Stern
Author: Jan Wasowicz
Author: Richard S. Sutton
Author: Jennifer Robbins
Author: Leslie Haley Wasserman
Author: Barbara Oakley, PhD
Author: Grant P. Wiggins
Author: Johannes Fürnkranz