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Deep Learning

Deep Learning
Author: Ian Goodfellow
Publisher: MIT Press
Total Pages: 801
Release: 2016-11-10
Genre: Computers
ISBN: 0262337371
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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.

Free Learning

Free Learning
Author: Ross Parker
Publisher: Routledge
Total Pages: 369
Release: 2021-11-29
Genre: Education
ISBN: 100048369X
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This edited volume explores, investigates and analyses Free Learning – an innovative approach to student-directed learning which seeks to challenge educational norms from within. The volume is framed by a recognition of the urgent need for transformation of our educational systems. In traditional education, students work through a teacher-directed linear syllabus, at a pace dictated by the teacher, with summative assessment hurdles at too-frequent intervals. Progression and direction are determined solely by the teacher. In Free Learning, students determine their own learning pathway through a non-linear syllabus, which can be visualised as a mind map. Students may then complete as many units as they either have time for or are interested in, moving from one unit to another on the basis of having formatively satisfied the demands of each individual unit. This volume showcases the value and potential of Free Learning in contemporary practice and is intended to bridge theory and practice. The structure of the book reflects this complementary fit, with contributions from practitioners describing Free Learning as a learning and teaching tool in a range of educational settings, subjects and age-ranges. It also contains qualitative and quantitative analyses by researchers exploring the uptake of Free Learning and students’ responses to the methodology. Researchers and educators who are interested in student-directed methodologies, especially in Asia, will find that the practical accounts and analyses of Free Learning contained within provide much food for thought with regard to redefining student learning.

An Introduction to Statistical Learning

An Introduction to Statistical Learning
Author: Gareth James
Publisher: Springer Nature
Total Pages: 617
Release: 2023-08-01
Genre: Mathematics
ISBN: 3031387473
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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.

Learning How to Learn

Learning How to Learn
Author: Barbara Oakley, PhD
Publisher: Penguin
Total Pages: 256
Release: 2018-08-07
Genre: Juvenile Nonfiction
ISBN: 052550446X
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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.

Universal Design for Learning

Universal Design for Learning
Author: Anne Meyer
Publisher: CAST Professional Publishing
Total Pages: 234
Release: 2015-12
Genre: Education
ISBN: 9781930583542
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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. --

Free to Learn

Free to Learn
Author: Peter Gray
Publisher: Basic Books
Total Pages: 227
Release: 2013-03-05
Genre: Education
ISBN: 0465037917
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A leading expert in childhood development makes the case for why self-directed learning -- "unschooling" -- is the best way to get kids to learn. In Free to Learn, developmental psychologist Peter Gray argues that in order to foster children who will thrive in today's constantly changing world, we must entrust them to steer their own learning and development. Drawing on evidence from anthropology, psychology, and history, he demonstrates that free play is the primary means by which children learn to control their lives, solve problems, get along with peers, and become emotionally resilient. A brave, counterintuitive proposal for freeing our children from the shackles of the curiosity-killing institution we call school, Free to Learn suggests that it's time to stop asking what's wrong with our children, and start asking what's wrong with the system. It shows how we can act—both as parents and as members of society—to improve children's lives and to promote their happiness and learning.

Deep Learning for Coders with fastai and PyTorch

Deep Learning for Coders with fastai and PyTorch
Author: Jeremy Howard
Publisher: O'Reilly Media
Total Pages: 624
Release: 2020-06-29
Genre: Computers
ISBN: 1492045497
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Deep learning is often viewed as the exclusive domain of math PhDs and big tech companies. But as this hands-on guide demonstrates, programmers comfortable with Python can achieve impressive results in deep learning with little math background, small amounts of data, and minimal code. How? With fastai, the first library to provide a consistent interface to the most frequently used deep learning applications. Authors Jeremy Howard and Sylvain Gugger, the creators of fastai, show you how to train a model on a wide range of tasks using fastai and PyTorch. You’ll also dive progressively further into deep learning theory to gain a complete understanding of the algorithms behind the scenes. Train models in computer vision, natural language processing, tabular data, and collaborative filtering Learn the latest deep learning techniques that matter most in practice Improve accuracy, speed, and reliability by understanding how deep learning models work Discover how to turn your models into web applications Implement deep learning algorithms from scratch Consider the ethical implications of your work Gain insight from the foreword by PyTorch cofounder, Soumith Chintala

Free-choice Learning and the Environment

Free-choice Learning and the Environment
Author: John Howard Falk
Publisher: Rowman Altamira
Total Pages: 224
Release: 2009
Genre: Education
ISBN: 0759111227
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Free-Choice Learning and the Environment explores the theoretical, practical, and policy aspects of free-choice environmental education for learners of all ages.

Learning to Bake Allergen-Free: A Crash Course for Busy Parents on Baking without Wheat, Gluten, Dairy, Eggs, Soy or Nuts

Learning to Bake Allergen-Free: A Crash Course for Busy Parents on Baking without Wheat, Gluten, Dairy, Eggs, Soy or Nuts
Author: Colette Martin
Publisher: The Experiment, LLC
Total Pages: 305
Release: 2012-06-19
Genre: Cooking
ISBN: 161519150X
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A crash course for busy parents on baking without wheat, gluten, dairy, eggs, soy, or nuts Has your child been diagnosed with food allergies? If so, help is here! Colette Martin has been there too: When her son Patrick was diagnosed with multiple food allergies in 2001, she had to learn all-new ways to feed him—and especially to make baked goods that he both could and would eat. Learning to Bake Allergen-Free is the book Colette Martin wishes she had back then. She ingeniously presents a dozen manageable lessons that will arm parents to prepare allergen-free baked goods the entire family can enjoy together. The book features: • More than 70 recipes (including variations) sure to become family staples—for muffins, rolls, breads, cookies, bars, scones, cakes, tarts, pizza, and pies— starting with the easiest techniques and adding new skills along the way • Clear explanations of the most common allergens and gluten, with all the details you need on which substitutions work, and why • Hundreds of simple tips for adapting recipes and troubleshooting as you go • Detailed guidelines and more than 15 recipes for making allergen-free treats from packaged gluten-free baking mixes • Special crash courses focused on key ingredients and techniques, including sweetening options, decorating a cake simply but superbly, kicking everyday recipes up a notch, and much more! Whether you already love to bake or are a kitchen novice, Learning to Bake Allergen-Free will give you the knowledge, skills, recipes, and confidence to make food that your family can safely eat—and that they’ll love!

Learning by Heart

Learning by Heart
Author: Corita Kent
Publisher: Simon and Schuster
Total Pages: 377
Release: 2008-10-14
Genre: Art
ISBN: 1621535908
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Tap into your natural ability to create! Engaging, proven exercises for developing creativity Priceless resource for teachers, artists, actors, everyone Artist and educator Corita Kent inspired generations of artists, and the truth of her words "We can all talk, we can all write, and if the blocks are removed, we can all draw and paint and make things" still shines through. This revised edition of her classic work Learning by Heart features a new foreword and a chart of curriculum standards. Kent's original projects and exercises, developed through more than 30 years as an art teacher and richly illustrated with 300 thought-provoking images, are as inspiring and as freeing today as they were during her lifetime. Learn how to challenge fears, be open to new directions, recognize connections between objects and ideas, and much more in this remarkable, indispensable guide to freeing the creative spirit within all of us. With new material by art world heavyweights Susan Friel and Barbara Loste, Learning by Heart brings creative inspiration into the 21st century!