SPELL-Links to Reading and Writing PDF Download
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Author: Jan Wasowicz
Publisher:
ISBN: 9780971513310
Category : English language
Languages : en
Pages :
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Book Description
Author: Jan Wasowicz
Publisher:
ISBN: 9780971513310
Category : English language
Languages : en
Pages :
Get Book Here
Book Description
Author: Andrea DeBruin-Parecki
Publisher: Wadsworth Publishing Company
ISBN: 9781573791434
Category : English language
Languages : en
Pages : 0
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Book Description
Suitable for all early childhood educators and practitioners, Letter Links is all about the alphabetic principle from a child development point of view. It highlights the importance of using symbols in preschool along with printed letters. Letter Links takes childrenÂ's natural interest in learning to write their own name as an entryway to teaching them letter recognition skills, letter-sound correspondence, and letter/word writing by using nametags and letter-linked images. The authors also provide eight specific teaching strategies. Letter Links outlines the research behind the learning system and provides detailed examples of 64 initial letter sounds represented by 26 letters. These are the letter combinations you need to introduce the bookÂ's more than 25 fun-filled activities that involve the alphabetic principle, phonological awareness, sense of word, and vocabulary.
Author: National Institute on Out-of-School Time (U.S.)
Publisher: Ingram
ISBN:
Category : Education
Languages : en
Pages : 188
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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: Ian Goodfellow
Publisher: MIT Press
ISBN: 0262337371
Category : Computers
Languages : en
Pages : 801
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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: Leslie Haley Wasserman
Publisher: Springer Science & Business Media
ISBN: 9400766718
Category : Education
Languages : en
Pages : 226
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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:
Publisher:
ISBN:
Category : Language arts (Elementary)
Languages : en
Pages : 104
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Book Description
Author: Josh Kaufman
Publisher: Penguin
ISBN: 1101623047
Category : Self-Help
Languages : en
Pages : 290
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Book Description
Forget the 10,000 hour rule— what if it’s possible to learn the basics of any new skill in 20 hours or less? Take a moment to consider how many things you want to learn to do. What’s on your list? What’s holding you back from getting started? Are you worried about the time and effort it takes to acquire new skills—time you don’t have and effort you can’t spare? Research suggests it takes 10,000 hours to develop a new skill. In this nonstop world when will you ever find that much time and energy? To make matters worse, the early hours of practicing something new are always the most frustrating. That’s why it’s difficult to learn how to speak a new language, play an instrument, hit a golf ball, or shoot great photos. It’s so much easier to watch TV or surf the web . . . In The First 20 Hours, Josh Kaufman offers a systematic approach to rapid skill acquisition— how to learn any new skill as quickly as possible. His method shows you how to deconstruct complex skills, maximize productive practice, and remove common learning barriers. By completing just 20 hours of focused, deliberate practice you’ll go from knowing absolutely nothing to performing noticeably well. Kaufman personally field-tested the methods in this book. You’ll have a front row seat as he develops a personal yoga practice, writes his own web-based computer programs, teaches himself to touch type on a nonstandard keyboard, explores the oldest and most complex board game in history, picks up the ukulele, and learns how to windsurf. Here are a few of the simple techniques he teaches: Define your target performance level: Figure out what your desired level of skill looks like, what you’re trying to achieve, and what you’ll be able to do when you’re done. The more specific, the better. Deconstruct the skill: Most of the things we think of as skills are actually bundles of smaller subskills. If you break down the subcomponents, it’s easier to figure out which ones are most important and practice those first. Eliminate barriers to practice: Removing common distractions and unnecessary effort makes it much easier to sit down and focus on deliberate practice. Create fast feedback loops: Getting accurate, real-time information about how well you’re performing during practice makes it much easier to improve. Whether you want to paint a portrait, launch a start-up, fly an airplane, or juggle flaming chainsaws, The First 20 Hours will help you pick up the basics of any skill in record time . . . and have more fun along the way.
Author: Diana Oblinger
Publisher:
ISBN:
Category : Academic libraries
Languages : es
Pages : 470
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Book Description
El espacio, ya sea físico o virtual, puede tener un impacto significativo en el aprendizaje. Learning Spaces se centra en la forma en que las expectativas de los alumnos influyen en dichos espacios, en los principios y actividades que facilitan el aprendizaje y en el papel de la tecnología desde la perspectiva de quienes crean los entornos de aprendizaje: profesores, tecnólogos del aprendizaje, bibliotecarios y administradores. La tecnología de la información ha aportado capacidades únicas a los espacios de aprendizaje, ya sea estimulando una mayor interacción mediante el uso de herramientas de colaboración, videoconferencias con expertos internacionales o abriendo mundos virtuales para la exploración. Este libro representa una exploración continua a medida que unimos el espacio, la tecnología y la pedagogía para asegurar el éxito de los estudiantes.
Author: Gareth James
Publisher: Springer Nature
ISBN: 3031387473
Category : Mathematics
Languages : en
Pages : 617
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Book 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, marketing, and 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. This book is targeted at statisticians and non-statisticians alike, who wish to use cutting-edge statistical learning techniques to analyze their data. Four of the authors co-wrote An Introduction to Statistical Learning, With Applications in R (ISLR), which has become a mainstay of undergraduate and graduate classrooms worldwide, as well as an important reference book for data scientists. One of the keys to its success was that each chapter contains a tutorial on implementing the analyses and methods presented in the R scientific computing environment. However, in recent years Python has become a popular language for data science, and there has been increasing demand for a Python-based alternative to ISLR. Hence, this book (ISLP) covers the same materials as ISLR but with labs implemented in Python. These labs will be useful both for Python novices, as well as experienced users.
Author: Richard S. Sutton
Publisher: MIT Press
ISBN: 0262352702
Category : Computers
Languages : en
Pages : 549
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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.
