Learning By Example

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Cognitive Psychology and Instruction

Author : Alan Lesgold
Publisher : Springer Science & Business Media
ISBN 13 : 1468425358
Total Pages : 517 pages
Book Rating : 4.4/5 (684 download)

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Book Synopsis Cognitive Psychology and Instruction by : Alan Lesgold

Download or read book Cognitive Psychology and Instruction written by Alan Lesgold and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 517 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sipke D. Fokkema Amsterdam, Free University From June 13th - 17th, 1977 the NATO International Conference on Cognitive Psychology and Instruction, organized by the editors of this volume, took place at the Free University of Amsterdam. During this period approximately 150 psychologists representing 15 countries assembled for an exchange of scientific experiences and ideas. The broad aim of the conference, as indicated by its title, was to explore the extent to which theoretical and methodological developments in cognitive psychology might provide useful knowledge with regard to the design and management of instruction. From a great variety of submitted papers the organizers attempted to select those that represented major problem areas being scientifically studied in several countries. For the organization of this book we chose to categorize the contributions according to the following general areas: I. Learning II. Comprehension and Information Structure III. Perceptual and Memory Processes in Reading IV. Problem Solving and Components of Intelligence V. Cognitive Development VI. Approaches to Instruction The final paper in the volume is an extensive review and summary by Glaser, Pellegrino, and Lesgold, that examines the state Qf cognitive psychology (mainly as reflected in the contributions in this volume) with regard to instructional purposes. Each of the sections of the book also begins with a brief overview of the specific topics considered by the individual contributors within that section.

Deep Learning By Example

Author : Ahmed Menshawy
Publisher : Packt Publishing Ltd
ISBN 13 : 178839576X
Total Pages : 442 pages
Book Rating : 4.7/5 (883 download)

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Book Synopsis Deep Learning By Example by : Ahmed Menshawy

Download or read book Deep Learning By Example written by Ahmed Menshawy and published by Packt Publishing Ltd. This book was released on 2018-02-28 with total page 442 pages. Available in PDF, EPUB and Kindle. Book excerpt: Grasp the fundamental concepts of deep learning using Tensorflow in a hands-on manner Key Features Get a first-hand experience of the deep learning concepts and techniques with this easy-to-follow guide Train different types of neural networks using Tensorflow for real-world problems in language processing, computer vision, transfer learning, and more Designed for those who believe in the concept of 'learn by doing', this book is a perfect blend of theory and code examples Book Description Deep learning is a popular subset of machine learning, and it allows you to build complex models that are faster and give more accurate predictions. This book is your companion to take your first steps into the world of deep learning, with hands-on examples to boost your understanding of the topic. This book starts with a quick overview of the essential concepts of data science and machine learning which are required to get started with deep learning. It introduces you to Tensorflow, the most widely used machine learning library for training deep learning models. You will then work on your first deep learning problem by training a deep feed-forward neural network for digit classification, and move on to tackle other real-world problems in computer vision, language processing, sentiment analysis, and more. Advanced deep learning models such as generative adversarial networks and their applications are also covered in this book. By the end of this book, you will have a solid understanding of all the essential concepts in deep learning. With the help of the examples and code provided in this book, you will be equipped to train your own deep learning models with more confidence. What you will learn Understand the fundamentals of deep learning and how it is different from machine learning Get familiarized with Tensorflow, one of the most popular libraries for advanced machine learning Increase the predictive power of your model using feature engineering Understand the basics of deep learning by solving a digit classification problem of MNIST Demonstrate face generation based on the CelebA database, a promising application of generative models Apply deep learning to other domains like language modeling, sentiment analysis, and machine translation Who this book is for This book targets data scientists and machine learning developers who wish to get started with deep learning. If you know what deep learning is but are not quite sure of how to use it, this book will help you as well. An understanding of statistics and data science concepts is required. Some familiarity with Python programming will also be beneficial.

Python Machine Learning By Example

Author : Yuxi (Hayden) Liu
Publisher : Packt Publishing Ltd
ISBN 13 : 178355312X
Total Pages : 249 pages
Book Rating : 4.7/5 (835 download)

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Book Synopsis Python Machine Learning By Example by : Yuxi (Hayden) Liu

Download or read book Python Machine Learning By Example written by Yuxi (Hayden) Liu and published by Packt Publishing Ltd. This book was released on 2017-05-31 with total page 249 pages. Available in PDF, EPUB and Kindle. Book excerpt: Take tiny steps to enter the big world of data science through this interesting guide About This Book Learn the fundamentals of machine learning and build your own intelligent applications Master the art of building your own machine learning systems with this example-based practical guide Work with important classification and regression algorithms and other machine learning techniques Who This Book Is For This book is for anyone interested in entering the data science stream with machine learning. Basic familiarity with Python is assumed. What You Will Learn Exploit the power of Python to handle data extraction, manipulation, and exploration techniques Use Python to visualize data spread across multiple dimensions and extract useful features Dive deep into the world of analytics to predict situations correctly Implement machine learning classification and regression algorithms from scratch in Python Be amazed to see the algorithms in action Evaluate the performance of a machine learning model and optimize it Solve interesting real-world problems using machine learning and Python as the journey unfolds In Detail Data science and machine learning are some of the top buzzwords in the technical world today. A resurging interest in machine learning is due to the same factors that have made data mining and Bayesian analysis more popular than ever. This book is your entry point to machine learning. This book starts with an introduction to machine learning and the Python language and shows you how to complete the setup. Moving ahead, you will learn all the important concepts such as, exploratory data analysis, data preprocessing, feature extraction, data visualization and clustering, classification, regression and model performance evaluation. With the help of various projects included, you will find it intriguing to acquire the mechanics of several important machine learning algorithms – they are no more obscure as they thought. Also, you will be guided step by step to build your own models from scratch. Toward the end, you will gather a broad picture of the machine learning ecosystem and best practices of applying machine learning techniques. Through this book, you will learn to tackle data-driven problems and implement your solutions with the powerful yet simple language, Python. Interesting and easy-to-follow examples, to name some, news topic classification, spam email detection, online ad click-through prediction, stock prices forecast, will keep you glued till you reach your goal. Style and approach This book is an enticing journey that starts from the very basics and gradually picks up pace as the story unfolds. Each concept is first succinctly defined in the larger context of things, followed by a detailed explanation of their application. Every concept is explained with the help of a project that solves a real-world problem, and involves hands-on work—giving you a deep insight into the world of machine learning. With simple yet rich language—Python—you will understand and be able to implement the examples with ease.

Learning SAS by Example

Author : Ron Cody
Publisher : SAS Institute
ISBN 13 : 1635266564
Total Pages : 553 pages
Book Rating : 4.6/5 (352 download)

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Book Synopsis Learning SAS by Example by : Ron Cody

Download or read book Learning SAS by Example written by Ron Cody and published by SAS Institute. This book was released on 2018-07-03 with total page 553 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learn to program SAS by example! Learning SAS by Example, A Programmer’s Guide, Second Edition, teaches SAS programming from very basic concepts to more advanced topics. Because most programmers prefer examples rather than reference-type syntax, this book uses short examples to explain each topic. The second edition has brought this classic book on SAS programming up to the latest SAS version, with new chapters that cover topics such as PROC SGPLOT and Perl regular expressions. This book belongs on the shelf (or e-book reader) of anyone who programs in SAS, from those with little programming experience who want to learn SAS to intermediate and even advanced SAS programmers who want to learn new techniques or identify new ways to accomplish existing tasks. In an instructive and conversational tone, author Ron Cody clearly explains each programming technique and then illustrates it with one or more real-life examples, followed by a detailed description of how the program works. The text is divided into four major sections: Getting Started, DATA Step Processing, Presenting and Summarizing Your Data, and Advanced Topics. Subjects addressed include Reading data from external sources Learning details of DATA step programming Subsetting and combining SAS data sets Understanding SAS functions and working with arrays Creating reports with PROC REPORT and PROC TABULATE Getting started with the SAS macro language Leveraging PROC SQL Generating high-quality graphics Using advanced features of user-defined formats and informats Restructuring SAS data sets Working with multiple observations per subject Getting started with Perl regular expressions You can test your knowledge and hone your skills by solving the problems at the end of each chapter.

Python by Example

Author : Nichola Lacey
Publisher : Cambridge University Press
ISBN 13 : 1108716830
Total Pages : 190 pages
Book Rating : 4.1/5 (87 download)

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Book Synopsis Python by Example by : Nichola Lacey

Download or read book Python by Example written by Nichola Lacey and published by Cambridge University Press. This book was released on 2019-06-06 with total page 190 pages. Available in PDF, EPUB and Kindle. Book excerpt: A refreshingly different and engaging way of learning how to program using Python. This book includes example code and brief user-friendly explanations, along with 150 progressively trickier challenges. As readers are actively involved in their learning, they quickly master the new skills and gain confidence in creating their own programs.

Python Machine Learning By Example

Author : Yuxi (Hayden) Liu
Publisher : Packt Publishing Ltd
ISBN 13 : 1800203861
Total Pages : 527 pages
Book Rating : 4.8/5 (2 download)

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Book Synopsis Python Machine Learning By Example by : Yuxi (Hayden) Liu

Download or read book Python Machine Learning By Example written by Yuxi (Hayden) Liu and published by Packt Publishing Ltd. This book was released on 2020-10-30 with total page 527 pages. Available in PDF, EPUB and Kindle. Book excerpt: A comprehensive guide to get you up to speed with the latest developments of practical machine learning with Python and upgrade your understanding of machine learning (ML) algorithms and techniques Key FeaturesDive into machine learning algorithms to solve the complex challenges faced by data scientists todayExplore cutting edge content reflecting deep learning and reinforcement learning developmentsUse updated Python libraries such as TensorFlow, PyTorch, and scikit-learn to track machine learning projects end-to-endBook Description Python Machine Learning By Example, Third Edition serves as a comprehensive gateway into the world of machine learning (ML). With six new chapters, on topics including movie recommendation engine development with Naïve Bayes, recognizing faces with support vector machine, predicting stock prices with artificial neural networks, categorizing images of clothing with convolutional neural networks, predicting with sequences using recurring neural networks, and leveraging reinforcement learning for making decisions, the book has been considerably updated for the latest enterprise requirements. At the same time, this book provides actionable insights on the key fundamentals of ML with Python programming. Hayden applies his expertise to demonstrate implementations of algorithms in Python, both from scratch and with libraries. Each chapter walks through an industry-adopted application. With the help of realistic examples, you will gain an understanding of the mechanics of ML techniques in areas such as exploratory data analysis, feature engineering, classification, regression, clustering, and NLP. By the end of this ML Python book, you will have gained a broad picture of the ML ecosystem and will be well-versed in the best practices of applying ML techniques to solve problems. What you will learnUnderstand the important concepts in ML and data scienceUse Python to explore the world of data mining and analyticsScale up model training using varied data complexities with Apache SparkDelve deep into text analysis and NLP using Python libraries such NLTK and GensimSelect and build an ML model and evaluate and optimize its performanceImplement ML algorithms from scratch in Python, TensorFlow 2, PyTorch, and scikit-learnWho this book is for If you’re a machine learning enthusiast, data analyst, or data engineer highly passionate about machine learning and want to begin working on machine learning assignments, this book is for you. Prior knowledge of Python coding is assumed and basic familiarity with statistical concepts will be beneficial, although this is not necessary.

International Handbook of the Learning Sciences

Author : Frank Fischer
Publisher : Routledge
ISBN 13 : 1317208358
Total Pages : 552 pages
Book Rating : 4.3/5 (172 download)

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Book Synopsis International Handbook of the Learning Sciences by : Frank Fischer

Download or read book International Handbook of the Learning Sciences written by Frank Fischer and published by Routledge. This book was released on 2018-04-19 with total page 552 pages. Available in PDF, EPUB and Kindle. Book excerpt: The International Handbook of the Learning Sciences is a comprehensive collection of international perspectives on this interdisciplinary field. In more than 50 chapters, leading experts synthesize past, current, and emerging theoretical and empirical directions for learning sciences research. The three sections of the handbook capture, respectively: foundational contributions from multiple disciplines and the ways in which the learning sciences has fashioned these into its own brand of use-oriented theory, design, and evidence; learning sciences approaches to designing, researching, and evaluating learning broadly construed; and the methodological diversity of learning sciences research, assessment, and analytic approaches. This pioneering collection is the definitive volume of international learning sciences scholarship and an essential text for scholars in this area.

The Cambridge Handbook of Cognition and Education

Author : John Dunlosky
Publisher : Cambridge University Press
ISBN 13 : 1108245102
Total Pages : 1130 pages
Book Rating : 4.1/5 (82 download)

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Book Synopsis The Cambridge Handbook of Cognition and Education by : John Dunlosky

Download or read book The Cambridge Handbook of Cognition and Education written by John Dunlosky and published by Cambridge University Press. This book was released on 2019-02-07 with total page 1130 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Handbook reviews a wealth of research in cognitive and educational psychology that investigates how to enhance learning and instruction to aid students struggling to learn and to advise teachers on how best to support student learning. The Handbook includes features that inform readers about how to improve instruction and student achievement based on scientific evidence across different domains, including science, mathematics, reading and writing. Each chapter supplies a description of the learning goal, a balanced presentation of the current evidence about the efficacy of various approaches to obtaining that learning goal, and a discussion of important future directions for research in this area. It is the ideal resource for researchers continuing their study of this field or for those only now beginning to explore how to improve student achievement.

How People Learn

Author : National Research Council
Publisher : National Academies Press
ISBN 13 : 0309131979
Total Pages : 386 pages
Book Rating : 4.3/5 (91 download)

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Book Synopsis How People Learn by : National Research Council

Download or read book How People Learn written by National Research Council and published by National Academies Press. This book was released on 2000-08-11 with total page 386 pages. Available in PDF, EPUB and Kindle. Book excerpt: First released in the Spring of 1999, How People Learn has been expanded to show how the theories and insights from the original book can translate into actions and practice, now making a real connection between classroom activities and learning behavior. This edition includes far-reaching suggestions for research that could increase the impact that classroom teaching has on actual learning. Like the original edition, this book offers exciting new research about the mind and the brain that provides answers to a number of compelling questions. When do infants begin to learn? How do experts learn and how is this different from non-experts? What can teachers and schools do-with curricula, classroom settings, and teaching methodsâ€"to help children learn most effectively? New evidence from many branches of science has significantly added to our understanding of what it means to know, from the neural processes that occur during learning to the influence of culture on what people see and absorb. How People Learn examines these findings and their implications for what we teach, how we teach it, and how we assess what our children learn. The book uses exemplary teaching to illustrate how approaches based on what we now know result in in-depth learning. This new knowledge calls into question concepts and practices firmly entrenched in our current education system. Topics include: How learning actually changes the physical structure of the brain. How existing knowledge affects what people notice and how they learn. What the thought processes of experts tell us about how to teach. The amazing learning potential of infants. The relationship of classroom learning and everyday settings of community and workplace. Learning needs and opportunities for teachers. A realistic look at the role of technology in education.

Interpretable Machine Learning

Author : Christoph Molnar
Publisher : Lulu.com
ISBN 13 : 0244768528
Total Pages : 320 pages
Book Rating : 4.2/5 (447 download)

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Book Synopsis Interpretable Machine Learning by : Christoph Molnar

Download or read book Interpretable Machine Learning written by Christoph Molnar and published by Lulu.com. This book was released on 2020 with total page 320 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Universal Design for Learning in the Classroom

Author : Tracey E. Hall
Publisher : Guilford Press
ISBN 13 : 1462506313
Total Pages : 177 pages
Book Rating : 4.4/5 (625 download)

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Book Synopsis Universal Design for Learning in the Classroom by : Tracey E. Hall

Download or read book Universal Design for Learning in the Classroom written by Tracey E. Hall and published by Guilford Press. This book was released on 2012-07-31 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: "Clearly written and well organized, this book shows how to apply the principles of universal design for learning (UDL) across all subject areas and grade levels. The editors and contributors describe practical ways to develop classroom goals, assessments, materials, and methods that use UDL to meet the needs of all learners. Specific teaching ideas are presented for reading, writing, science, mathematics, history, and the arts, including detailed examples and troubleshooting tips. Particular attention is given to how UDL can inform effective, innovative uses of technology in the inclusive classroom. Subject Areas/Keywords: assessments, classrooms, content areas, curriculum design, digital media, educational technology, elementary, inclusion, instruction, learning disabilities, literacy, schools, secondary, special education, supports, teaching methods, UDL, universal design Audience: General and special educators in grades K-8, literacy specialists, school psychologists, administrators, teacher educators, and graduate students"--

How Learning Works

Author : Susan A. Ambrose
Publisher : John Wiley & Sons
ISBN 13 : 0470617608
Total Pages : 336 pages
Book Rating : 4.4/5 (76 download)

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Book Synopsis How Learning Works by : Susan A. Ambrose

Download or read book How Learning Works written by Susan A. Ambrose and published by John Wiley & Sons. This book was released on 2010-04-16 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: Praise for How Learning Works "How Learning Works is the perfect title for this excellent book. Drawing upon new research in psychology, education, and cognitive science, the authors have demystified a complex topic into clear explanations of seven powerful learning principles. Full of great ideas and practical suggestions, all based on solid research evidence, this book is essential reading for instructors at all levels who wish to improve their students' learning." —Barbara Gross Davis, assistant vice chancellor for educational development, University of California, Berkeley, and author, Tools for Teaching "This book is a must-read for every instructor, new or experienced. Although I have been teaching for almost thirty years, as I read this book I found myself resonating with many of its ideas, and I discovered new ways of thinking about teaching." —Eugenia T. Paulus, professor of chemistry, North Hennepin Community College, and 2008 U.S. Community Colleges Professor of the Year from The Carnegie Foundation for the Advancement of Teaching and the Council for Advancement and Support of Education "Thank you Carnegie Mellon for making accessible what has previously been inaccessible to those of us who are not learning scientists. Your focus on the essence of learning combined with concrete examples of the daily challenges of teaching and clear tactical strategies for faculty to consider is a welcome work. I will recommend this book to all my colleagues." —Catherine M. Casserly, senior partner, The Carnegie Foundation for the Advancement of Teaching "As you read about each of the seven basic learning principles in this book, you will find advice that is grounded in learning theory, based on research evidence, relevant to college teaching, and easy to understand. The authors have extensive knowledge and experience in applying the science of learning to college teaching, and they graciously share it with you in this organized and readable book." —From the Foreword by Richard E. Mayer, professor of psychology, University of California, Santa Barbara; coauthor, e-Learning and the Science of Instruction; and author, Multimedia Learning

R Machine Learning By Example

Author : Raghav Bali
Publisher : Packt Publishing Ltd
ISBN 13 : 1784392634
Total Pages : 340 pages
Book Rating : 4.7/5 (843 download)

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Book Synopsis R Machine Learning By Example by : Raghav Bali

Download or read book R Machine Learning By Example written by Raghav Bali and published by Packt Publishing Ltd. This book was released on 2016-03-31 with total page 340 pages. Available in PDF, EPUB and Kindle. Book excerpt: Understand the fundamentals of machine learning with R and build your own dynamic algorithms to tackle complicated real-world problems successfully About This Book Get to grips with the concepts of machine learning through exciting real-world examples Visualize and solve complex problems by using power-packed R constructs and its robust packages for machine learning Learn to build your own machine learning system with this example-based practical guide Who This Book Is For If you are interested in mining useful information from data using state-of-the-art techniques to make data-driven decisions, this is a go-to guide for you. No prior experience with data science is required, although basic knowledge of R is highly desirable. Prior knowledge in machine learning would be helpful but is not necessary. What You Will Learn Utilize the power of R to handle data extraction, manipulation, and exploration techniques Use R to visualize data spread across multiple dimensions and extract useful features Explore the underlying mathematical and logical concepts that drive machine learning algorithms Dive deep into the world of analytics to predict situations correctly Implement R machine learning algorithms from scratch and be amazed to see the algorithms in action Write reusable code and build complete machine learning systems from the ground up Solve interesting real-world problems using machine learning and R as the journey unfolds Harness the power of robust and optimized R packages to work on projects that solve real-world problems in machine learning and data science In Detail Data science and machine learning are some of the top buzzwords in the technical world today. From retail stores to Fortune 500 companies, everyone is working hard to making machine learning give them data-driven insights to grow their business. With powerful data manipulation features, machine learning packages, and an active developer community, R empowers users to build sophisticated machine learning systems to solve real-world data problems. This book takes you on a data-driven journey that starts with the very basics of R and machine learning and gradually builds upon the concepts to work on projects that tackle real-world problems. You'll begin by getting an understanding of the core concepts and definitions required to appreciate machine learning algorithms and concepts. Building upon the basics, you will then work on three different projects to apply the concepts of machine learning, following current trends and cover major algorithms as well as popular R packages in detail. These projects have been neatly divided into six different chapters covering the worlds of e-commerce, finance, and social-media, which are at the very core of this data-driven revolution. Each of the projects will help you to understand, explore, visualize, and derive insights depending upon the domain and algorithms. Through this book, you will learn to apply the concepts of machine learning to deal with data-related problems and solve them using the powerful yet simple language, R. Style and approach The book is an enticing journey that starts from the very basics to gradually pick up pace as the story unfolds. Each concept is first defined in the larger context of things succinctly, followed by a detailed explanation of their application. Each topic is explained with the help of a project that solves a real real-world problem involving hands-on work thus giving you a deep insight into the world of machine learning.

Learning by Example

Author : David Strang
Publisher : Princeton University Press
ISBN 13 : 069117119X
Total Pages : 301 pages
Book Rating : 4.6/5 (911 download)

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Book Synopsis Learning by Example by : David Strang

Download or read book Learning by Example written by David Strang and published by Princeton University Press. This book was released on 2016-06-28 with total page 301 pages. Available in PDF, EPUB and Kindle. Book excerpt: In business, as in other aspects of life, we learn and grow from the examples set by others. Imitation can lead to innovation. But in order to grow innovatively, how do businesses decide what firms to imitate? And how do they choose what practices to follow? Learning by Example takes an unprecedented look at the benchmarking initiative of a major financial institution. David Strang closely follows twenty-one teams of managers sent out to observe the practices of other companies in order to develop recommendations for change in their own organization. Through extensive interviews, surveys, and archival materials, Strang reveals that benchmarking promotes a distinctive managerial regime with potential benefits and pitfalls. He explores the organizations treated as models of best practice, the networks that surround a bank and form its reference group, the ways managers craft calls for change, and the programs implemented in the wake of vicarious learning. Strang finds that imitation does not occur through mindless conformity. Instead, managers act creatively, combining what they see in external site visits with their bank's strategic objectives, interpreted in light of their understanding of rational and progressive management. Learning by Example opens the black box of interorganizational diffusion to show how managers interpret, advocate, and implement innovations.

An Introduction to Statistical Learning

Author : Gareth James
Publisher : Springer Nature
ISBN 13 : 3031387473
Total Pages : 617 pages
Book Rating : 4.0/5 (313 download)

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Book Synopsis An Introduction to Statistical Learning by : Gareth James

Download or read book An Introduction to Statistical Learning written by Gareth James and published by Springer Nature. This book was released on 2023-08-01 with total page 617 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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

Author : Barbara Oakley, PhD
Publisher : Penguin
ISBN 13 : 052550446X
Total Pages : 258 pages
Book Rating : 4.5/5 (255 download)

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Book Synopsis Learning How to Learn by : Barbara Oakley, PhD

Download or read book Learning How to Learn written by Barbara Oakley, PhD and published by Penguin. This book was released on 2018-08-07 with total page 258 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Understanding by Design

Author : Grant P. Wiggins
Publisher : ASCD
ISBN 13 : 1416600353
Total Pages : 383 pages
Book Rating : 4.4/5 (166 download)

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Book Synopsis Understanding by Design by : Grant P. Wiggins

Download or read book Understanding by Design written by Grant P. Wiggins and published by ASCD. This book was released on 2005 with total page 383 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.