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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: Ian Goodfellow
Publisher: MIT Press
ISBN: 0262337371
Category : Computers
Languages : en
Pages : 801
Get Book
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: John Almarode
Publisher: Corwin Press
ISBN: 1506384722
Category : Education
Languages : en
Pages : 241
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Book Description
An essential resource for student and teacher clarity With the ever-changing landscape of education, teachers and leaders often find themselves searching for clarity in a sea of standards, curriculum resources, and competing priorities. Clarity for Learning offers a simple and doable approach to developing clarity and sharing it with students through five essential components: crafting learning intentions and success criteria co-constructing learning intentions and success criteria with learners creating opportunities for students to respond effective feedback on and for learning students and teachers sharing learning and progress The book is full of examples from teachers and leaders who have shared their journey, struggles, and successes for readers to use to propel their own work forward.
Author: Barbara Oakley, PhD
Publisher: Penguin
ISBN: 052550446X
Category : Juvenile Nonfiction
Languages : en
Pages : 256
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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: 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 DuFour
Publisher: Solution Tree Press
ISBN: 1935249894
Category : Education
Languages : en
Pages : 373
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Book Description
Like the first edition, the second edition of Learning by Doing: A Handbook for Professional Learning Communities at Work helps educators close the knowing-doing gap as they transform their schools into professional learning communities (PLCs).
Author: Anne Meyer
Publisher: CAST Professional Publishing
ISBN: 9781930583542
Category : Education
Languages : en
Pages : 234
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Book Description
Anne Meyer and David Rose, who first laid out the principles of UDL, provide an ambitious, engaging discussion of new research and best practices. This book gives the UDL field an essential and authoritative learning resource for the coming years. In the 1990s, Anne Meyer, David Rose, and their colleagues at CAST introduced Universal Design for Learning (UDL) as a framework to improve teaching and learning in the digital age, sparking an international reform movement. Now Meyer and Rose return with Universal Design for Learning: Theory and Practice, an up-to-date multimedia online book (with print and e-book options) that leverages more than a decade of research and implementation. This is the first significant new statement on UDL since 2002, an ambitious, engaging exploration of ideas and best practices that provides the growing UDL field with an essential and authoritative learning resource for the coming years. This new work includes contributions from CAST's research and implementation teams as well as from many of CAST's collaborators in schools, universities, and research settings. Readers are invited to contribute ideas, perspectives, and examples from their own practice in an online community of practice. --
Author: Carla Marschall
Publisher: Corwin Press
ISBN: 1071835920
Category : Education
Languages : en
Pages : 518
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Book Description
Nautilus Gold Award Winner (Books for a Better World) in Social Sciences & Education Create inclusive, democratic classrooms that prepare knowledgeable, compassionate, and engaged global citizens. Today’s global challenges—climate change, food and water insecurity, social and economic inequality, and a global pandemic—demand that educators prepare students to become compassionate, critical thinkers who can explore alternative futures. Their own, others’, and the planet’s well-being depend on it. Worldwise Learning presents a "Pedagogy for People, Planet, and Prosperity" that supports K-8 educators in nurturing "Worldwise Learners": students who both deeply understand and purposefully act when learning about global challenges. Coupling theory with practice, this book builds educators’ understanding of how curriculum and meaningful interdisciplinary learning can be organized around local, global, and intercultural issues, and provides a detailed framework for making those issues come alive in the classroom. Richly illustrated, each innovative chapter asserts a transformational approach to teaching and learning following an original three-part inquiry cycle, and includes: Practical classroom strategies to implement Worldwise Learning at the lesson level, along with tips for scaffolding students’ thinking. Images of student work and vignettes of learning experiences that help educators visualize authentic Worldwise Learning moments. Stories that spotlight Worldwise Learning in action from diverse student, teacher, and organization perspectives. An exemplar unit plan that illustrates how the planning process links to and can support teaching and learning about global challenges. QR codes that link to additional lesson and unit plans, educational resources, videos of strategies, and interviews with educators and thought leaders on a companion website, where teachers can discuss topics and share ideas with each other. Worldwise Learning turns students into local and global citizens who feel genuine concern for the world around them, living their learning with intention and purpose. The time is now.
Author: John Hattie
Publisher: Routledge
ISBN: 1134024126
Category : Education
Languages : en
Pages : 389
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Book Description
This unique and ground-breaking book is the result of 15 years research and synthesises over 800 meta-analyses on the influences on achievement in school-aged students. It builds a story about the power of teachers, feedback, and a model of learning and understanding. The research involves many millions of students and represents the largest ever evidence based research into what actually works in schools to improve learning. Areas covered include the influence of the student, home, school, curricula, teacher, and teaching strategies. A model of teaching and learning is developed based on the notion of visible teaching and visible learning. A major message is that what works best for students is similar to what works best for teachers – an attention to setting challenging learning intentions, being clear about what success means, and an attention to learning strategies for developing conceptual understanding about what teachers and students know and understand. Although the current evidence based fad has turned into a debate about test scores, this book is about using evidence to build and defend a model of teaching and learning. A major contribution is a fascinating benchmark/dashboard for comparing many innovations in teaching and schools.
Author: Monica R. Martinez
Publisher: The New Press
ISBN: 1620973979
Category : Education
Languages : en
Pages : 166
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Book Description
The acclaimed exploration of how public education can cultivate innovators—with a foreword by Russlynn Ali, a leading advocate for remaking schools Dime-a-dozen ideas for reforming education seem to be everywhere these days but few actually transform the everyday experience of the 50-million-plus students who are regularly subjected to traditional lecturing, note-taking, and rote learning—often with dismal results. Enter Deeper Learning, "a fast read [that] will interest educators who want to produce self-motivated, passionate learners" (Library Journal). Offering "uplifting" (Kirkus Reviews) anecdotes in what Tom Carroll of the National Commission on Teaching and America's Future calls a "rare blend of inspiration and practical action," Deeper Learning provides a blueprint for creating flexible environments that put students at the helm of their own collaborative learning experience. This paperback edition includes a new foreword by renowned education advocate Russlynn Ali and will empower and inspire educators everywhere to address the need for schools to be genuinely innovative.
Author: Linda Darling-Hammond
Publisher: John Wiley & Sons
ISBN: 1119181763
Category : Education
Languages : en
Pages : 288
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Book Description
In Powerful Learning, Linda Darling-Hammond and animpressive list of co-authors offer a clear, comprehensive, andengaging exploration of the most effective classroom practices.They review, in practical terms, teaching strategies that generatemeaningful K–2 student understanding, and occur both withinthe classroom walls and beyond. The book includes rich stories, aswell as online videos of innovative classrooms and schools, thatshow how students who are taught well are able to think critically,employ flexible problem-solving, and apply learned skills andknowledge to new situations.
