Learning

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Deep Learning

Ian Goodfellow,Yoshua Bengio,Aaron Courville
Deep Learning Book PDF

Author : Ian Goodfellow,Yoshua Bengio,Aaron Courville
Publisher : MIT Press
Page : 801 pages
File Size : 42,8 Mb
Release : 2016-11-10
Category : Computers
ISBN : 9780262337373

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Deep Learning by Ian Goodfellow,Yoshua Bengio,Aaron Courville Pdf

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.

Graph Representation Learning

William L. William L. Hamilton
Graph Representation Learning Book PDF

Author : William L. William L. Hamilton
Publisher : Springer Nature
Page : 141 pages
File Size : 44,6 Mb
Release : 2022-06-01
Category : Computers
ISBN : 9783031015885

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Graph Representation Learning by William L. William L. Hamilton Pdf

Graph-structured data is ubiquitous throughout the natural and social sciences, from telecommunication networks to quantum chemistry. Building relational inductive biases into deep learning architectures is crucial for creating systems that can learn, reason, and generalize from this kind of data. Recent years have seen a surge in research on graph representation learning, including techniques for deep graph embeddings, generalizations of convolutional neural networks to graph-structured data, and neural message-passing approaches inspired by belief propagation. These advances in graph representation learning have led to new state-of-the-art results in numerous domains, including chemical synthesis, 3D vision, recommender systems, question answering, and social network analysis. This book provides a synthesis and overview of graph representation learning. It begins with a discussion of the goals of graph representation learning as well as key methodological foundations in graph theory and network analysis. Following this, the book introduces and reviews methods for learning node embeddings, including random-walk-based methods and applications to knowledge graphs. It then provides a technical synthesis and introduction to the highly successful graph neural network (GNN) formalism, which has become a dominant and fast-growing paradigm for deep learning with graph data. The book concludes with a synthesis of recent advancements in deep generative models for graphs—a nascent but quickly growing subset of graph representation learning.

Reinforcement Learning, second edition

Richard S. Sutton,Andrew G. Barto
Reinforcement Learning second edition Book PDF

Author : Richard S. Sutton,Andrew G. Barto
Publisher : MIT Press
Page : 549 pages
File Size : 48,5 Mb
Release : 2018-11-13
Category : Computers
ISBN : 9780262352703

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Reinforcement Learning, second edition by Richard S. Sutton,Andrew G. Barto Pdf

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.

Interpretable Machine Learning

Christoph Molnar
Interpretable Machine Learning Book PDF

Author : Christoph Molnar
Publisher : Lulu.com
Page : 320 pages
File Size : 54,8 Mb
Release : 2020
Category : Artificial intelligence
ISBN : 9780244768522

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Interpretable Machine Learning by Christoph Molnar Pdf

This book is about making machine learning models and their decisions interpretable. After exploring the concepts of interpretability, you will learn about simple, interpretable models such as decision trees, decision rules and linear regression. Later chapters focus on general model-agnostic methods for interpreting black box models like feature importance and accumulated local effects and explaining individual predictions with Shapley values and LIME. All interpretation methods are explained in depth and discussed critically. How do they work under the hood? What are their strengths and weaknesses? How can their outputs be interpreted? This book will enable you to select and correctly apply the interpretation method that is most suitable for your machine learning project.

An Introduction to Statistical Learning

Gareth James,Daniela Witten,Trevor Hastie,Robert Tibshirani,Jonathan Taylor
An Introduction to Statistical Learning Book PDF

Author : Gareth James,Daniela Witten,Trevor Hastie,Robert Tibshirani,Jonathan Taylor
Publisher : Springer Nature
Page : 617 pages
File Size : 50,5 Mb
Release : 2023-08-01
Category : Mathematics
ISBN : 9783031387470

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An Introduction to Statistical Learning by Gareth James,Daniela Witten,Trevor Hastie,Robert Tibshirani,Jonathan Taylor Pdf

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.

Clarity for Learning

John Almarode,Kara Vandas
Clarity for Learning Book PDF

Author : John Almarode,Kara Vandas
Publisher : Corwin Press
Page : 241 pages
File Size : 52,7 Mb
Release : 2018-10-24
Category : Education
ISBN : 9781506384726

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Clarity for Learning by John Almarode,Kara Vandas Pdf

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.

Learning How to Learn

Barbara Oakley, PhD,Terrence Sejnowski, PhD,Alistair McConville
Learning How to Learn Book PDF

Author : Barbara Oakley, PhD,Terrence Sejnowski, PhD,Alistair McConville
Publisher : Penguin
Page : 256 pages
File Size : 46,8 Mb
Release : 2018-08-07
Category : Juvenile Nonfiction
ISBN : 9780525504467

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Learning How to Learn by Barbara Oakley, PhD,Terrence Sejnowski, PhD,Alistair McConville Pdf

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.

The Hundred-page Machine Learning Book

Andriy Burkov
The Hundred page Machine Learning Book Book PDF

Author : Andriy Burkov
Publisher : Unknown
Page : 141 pages
File Size : 41,6 Mb
Release : 2019
Category : Machine learning
ISBN : 199957950X

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The Hundred-page Machine Learning Book by Andriy Burkov Pdf

Provides a practical guide to get started and execute on machine learning within a few days without necessarily knowing much about machine learning.The first five chapters are enough to get you started and the next few chapters provide you a good feel of more advanced topics to pursue.

Situated Learning

Jean Lave,Etienne Wenger
Situated Learning Book PDF

Author : Jean Lave,Etienne Wenger
Publisher : Cambridge University Press
Page : 144 pages
File Size : 46,8 Mb
Release : 1991-09-27
Category : Education
ISBN : 0521423740

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Situated Learning by Jean Lave,Etienne Wenger Pdf

In this important theoretical treatist, the authors push forward the notion of situated learning - that learning is fundamentally a social process.

Long Life Learning

Michelle R. Weise
Long Life Learning Book PDF

Author : Michelle R. Weise
Publisher : John Wiley & Sons
Page : 272 pages
File Size : 49,9 Mb
Release : 2020-11-10
Category : Business & Economics
ISBN : 9781119597520

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Long Life Learning by Michelle R. Weise Pdf

A visionary guide for the future of learning and work Long Life Learning: Preparing for Jobs That Don’t Even Exist Yet offers readers a fascinating glimpse into a near-future where careers last 100 years, and education lasts a lifetime. The book makes the case that learners of the future are going to repeatedly seek out educational opportunities throughout the course of their working lives — which will no longer have a beginning, middle, and end. Long Life Learning focuses on the disruptive and burgeoning innovations that are laying the foundation for a new learning model that includes clear navigation, wraparound and funding supports, targeted education, and clear connections to more transparent hiring processes. Written by the former chief innovation officer of Strada Education Network’s Institute for the Future of Work, the book examines: How will a dramatically extended lifespan affect our careers? How will more time in the workforce shape our educational demands? Will a four-year degree earned at the start of a 100-year career adequately prepare us for the challenges ahead? Perfect for anyone with an interest in the future of education and Clayton Christensen’s theories of disruptive innovation, Long Life Learning provides an invaluable glimpse into a future that many of us have not even begun to imagine.

Mother of Learning: ARC 1

nobody103,Domagoj Kurmaic
Mother of Learning ARC 1 Book PDF

Author : nobody103,Domagoj Kurmaic
Publisher : Wraithmarked Creative, LLC
Page : 786 pages
File Size : 43,8 Mb
Release : 2021-12-01
Category : Fiction
ISBN : 9781955252096

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Mother of Learning: ARC 1 by nobody103,Domagoj Kurmaic Pdf

Zorian Kazinski has all the time in the world to get stronger, and he plans on taking full advantage of it. A teenage mage of humble birth and slightly above-average skill, Zorian is attending his third year of education at Cyoria's magical academy. A driven and quiet young man, he is consumed by a desire to ensure his own future and free himself of the influence of his family, resenting the Kazinskis for favoring his brothers over him. Consequently, Zorian has no time for pointless distractions, much less other people's problems. As it happens, though, time is something he is about to get plenty of. On the eve of Cyoria's annual summer festival, Zorian is murdered, then abruptly brought back to the beginning of the month, just before he was about to take the train to school. Finding himself trapped in a time loop with no clear end or exit, he will have to look both within and without to unravel the mystery set before him. He does have to unravel it, too, because the loop clearly wasn’t made for his sake, and in a world of magic even a time traveler isn't safe from those who wish him ill. Fortunately for Zorian, repetition is the mother of learning…

Experiential Learning

David A. Kolb
Experiential Learning Book PDF

Author : David A. Kolb
Publisher : FT Press
Page : 417 pages
File Size : 48,5 Mb
Release : 2014-12-17
Category : Business & Economics
ISBN : 9780133892505

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Experiential Learning by David A. Kolb Pdf

Experiential learning is a powerful and proven approach to teaching and learning that is based on one incontrovertible reality: people learn best through experience. Now, in this extensively updated book, David A. Kolb offers a systematic and up-to-date statement of the theory of experiential learning and its modern applications to education, work, and adult development. Experiential Learning, Second Edition builds on the intellectual origins of experiential learning as defined by figures such as John Dewey, Kurt Lewin, Jean Piaget, and L.S. Vygotsky, while also reflecting three full decades of research and practice since the classic first edition. Kolb models the underlying structures of the learning process based on the latest insights in psychology, philosophy, and physiology. Building on his comprehensive structural model, he offers an exceptionally useful typology of individual learning styles and corresponding structures of knowledge in different academic disciplines and careers. Kolb also applies experiential learning to higher education and lifelong learning, especially with regard to adult education. This edition reviews recent applications and uses of experiential learning, updates Kolb's framework to address the current organizational and educational landscape, and features current examples of experiential learning both in the field and in the classroom. It will be an indispensable resource for everyone who wants to promote more effective learning: in higher education, training, organizational development, lifelong learning environments, and online.

Learning to Die

Robert Bringhurst,Jan Zwicky
Learning to Die Book PDF

Author : Robert Bringhurst,Jan Zwicky
Publisher : Unknown
Page : 104 pages
File Size : 40,8 Mb
Release : 2018-10
Category : Philosophy
ISBN : 088977563X

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Learning to Die by Robert Bringhurst,Jan Zwicky Pdf

Two powerful writers draw upon philosophy to find a roadmap for grace and equanimity in the face of the death of our planet.

Learn to Drive Smart

ICBC
Learn to Drive Smart Book PDF

Author : ICBC
Publisher : ICBC
Page : 177 pages
File Size : 45,8 Mb
Release : 2024-05-26
Category : Study Aids
ISBN : 8210379456XXX

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Learn to Drive Smart by ICBC Pdf

Whether you are new to British Columbia, taking a re-examination, or brushing up on your driving skills, the Learn to Drive Smart guide gives you the basic information to help you drive safely. The guide will also help you prepare for the knowledge test, and Class 7 and Class 5 road tests. * Google Play may require a credit card to activate your account. ICBC does not collect your credit card information and the driving guides are free. Please see Google Play Terms of Service for more information.

Learning to Leave

Michael Corbett
Learning to Leave Book PDF

Author : Michael Corbett
Publisher : Rural Studies
Page : 312 pages
File Size : 45,9 Mb
Release : 2020
Category : Education
ISBN : 1949199533

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Learning to Leave by Michael Corbett Pdf

Published with a new preface, this innovative case study from Nova Scotia analyzes the relationship between rural communities and contemporary education. Rather than supporting place-sensitive curricula and establishing networks within community populations, the rural school has too often stood apart from local life, with the generally unintended consequence that many educationally successful rural youth come to see their communities and lifestyles as places to be left behind. They face what Michael Corbett calls a mobility imperative, which, he shows, has been central to contemporary schooling. Learning to Leave argues that if education is to be democratic and serve the purpose of economic, social, and cultural development, then it must adapt and respond to the specificity of its locale, the knowledge practices of the people, and the needs of those who struggle to remain in challenged rural places.