Targeted Learning
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Targeted Learning
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Author : Mark J. van der Laan
language : en
Publisher: Springer Science & Business Media
Release Date : 2011-06-17
Targeted Learning written by Mark J. van der Laan and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2011-06-17 with Mathematics categories.
The statistics profession is at a unique point in history. The need for valid statistical tools is greater than ever; data sets are massive, often measuring hundreds of thousands of measurements for a single subject. The field is ready to move towards clear objective benchmarks under which tools can be evaluated. Targeted learning allows (1) the full generalization and utilization of cross-validation as an estimator selection tool so that the subjective choices made by humans are now made by the machine, and (2) targeting the fitting of the probability distribution of the data toward the target parameter representing the scientific question of interest. This book is aimed at both statisticians and applied researchers interested in causal inference and general effect estimation for observational and experimental data. Part I is an accessible introduction to super learning and the targeted maximum likelihood estimator, including related concepts necessary to understand and apply these methods. Parts II-IX handle complex data structures and topics applied researchers will immediately recognize from their own research, including time-to-event outcomes, direct and indirect effects, positivity violations, case-control studies, censored data, longitudinal data, and genomic studies.
Deep Learning For Radar And Communications Automatic Target Recognition
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Author : Uttam K. Majumder
language : en
Publisher: Artech House
Release Date : 2020-07-31
Deep Learning For Radar And Communications Automatic Target Recognition written by Uttam K. Majumder and has been published by Artech House this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-07-31 with Technology & Engineering categories.
This authoritative resource presents a comprehensive illustration of modern Artificial Intelligence / Machine Learning (AI/ML) technology for radio frequency (RF) data exploitation. It identifies technical challenges, benefits, and directions of deep learning (DL) based object classification using radar data, including synthetic aperture radar (SAR) and high range resolution (HRR) radar. The performance of AI/ML algorithms is provided from an overview of machine learning (ML) theory that includes history, background primer, and examples. Radar data issues of collection, application, and examples for SAR/HRR data and communication signals analysis are discussed. In addition, this book presents practical considerations of deploying such techniques, including performance evaluation, energy-efficient computing, and the future unresolved issues.
The Brain Targeted Teaching Model For 21st Century Schools
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Author : Mariale M. Hardiman
language : en
Publisher: Corwin Press
Release Date : 2012-02-15
The Brain Targeted Teaching Model For 21st Century Schools written by Mariale M. Hardiman and has been published by Corwin Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-02-15 with Education categories.
A powerful guide for applying brain research for more effective instruction The Brain-Targeted Teaching Model for 21st-Century Schools serves as a bridge between research and practice by providing a cohesive, proven, and usable model of effective instruction. Compatible with other professional development programs, this model shows how to apply educational and cognitive neuroscience principles into classroom settings through a pedagogical framework. The model’s six components are: (1) Establish the emotional connection to learning (2) Develop the physical learning environment (3) Design the learning experience (4) Teach for the mastery of content, skills, and concepts (5) Teach for the extension and application of knowledge (6) Evaluate learning
Multiagent Systems
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Author : Yoav Shoham
language : en
Publisher: Cambridge University Press
Release Date : 2008-12-15
Multiagent Systems written by Yoav Shoham and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-12-15 with Computers categories.
Multiagent systems combine multiple autonomous entities, each having diverging interests or different information. This overview of the field offers a computer science perspective, but also draws on ideas from game theory, economics, operations research, logic, philosophy and linguistics. It will serve as a reference for researchers in each of these fields, and be used as a text for advanced undergraduate or graduate courses. The authors emphasize foundations to create a broad and rigorous treatment of their subject, with thorough presentations of distributed problem solving, game theory, multiagent communication and learning, social choice, mechanism design, auctions, cooperative game theory, and modal logics of knowledge and belief. For each topic, basic concepts are introduced, examples are given, proofs of key results are offered, and algorithmic considerations are examined. An appendix covers background material in probability theory, classical logic, Markov decision processes and mathematical programming.
Learning How To Learn
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Author : Barbara Oakley, PhD
language : en
Publisher: Penguin
Release Date : 2018-08-07
Learning How To Learn written by Barbara Oakley, PhD and has been published by Penguin this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-08-07 with Juvenile Nonfiction categories.
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.
Interpretable Machine Learning
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Author : Christoph Molnar
language : en
Publisher: Lulu.com
Release Date : 2020
Interpretable Machine Learning written by Christoph Molnar and has been published by Lulu.com this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020 with Computers categories.
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.
How To Grade For Learning
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Author : Ken O′Connor
language : en
Publisher: Corwin Press
Release Date : 2017-10-04
How To Grade For Learning written by Ken O′Connor and has been published by Corwin Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-04 with Education categories.
Implement standards-based grading practices that help students succeed! Classroom assessment and grading should help students grow and develop to their full potential, but meshing traditional grading practices with students’ achievement on standards has been difficult and daunting. Making real and lasting changes to grading practices requires both knowledge and willpower. This 4th edition of the best-selling How to Grade for Learning provides eight guidelines for good grading, offers recommendations for practical applications, and gives solid suggestions for implementing more effective grading practices. Ken O’Connor presents the latest research on motivation, mindset, learning styles, and beliefs about fairness to inform this new edition, which includes: Both the why’s and the how-to’s of implementing standards-based grading practices 48 educator contributions from nationally and internationally known educators, authors, and consultants that provide ideas and testimonials for effective assessment practices Sections on hot-button issues such as academic dishonesty, extra credit, bonus points and homework Additional information on utilizing levels of proficiency and eliminating the use of percentages and averaging Reflective exercises and numerous tools, including rubrics, sample letters, and case studies Techniques for managing grading more efficiently An invaluable resource for helping teachers assign grades that are accurate, consistent, meaningful, and supportive of learning, this book also makes an ideal staff development resource.
Towards Sustainable And Scalable Educational Innovations Informed By The Learning Sciences
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Author : Chee-Kit Looi
language : en
Publisher: IOS Press
Release Date : 2005
Towards Sustainable And Scalable Educational Innovations Informed By The Learning Sciences written by Chee-Kit Looi and has been published by IOS Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Computers categories.
One of the basic principles that underpin the learning sciences is to improve theories of learning through the design of powerful learning environments that can foster meaningful learning. Learning sciences researchers prefer to research learning in authentic contexts. This book focuses on learning sciences in the Asia-Pacific context.
Profiling Target Learners For The Development Of Effective Learning Strategies Emerging Research And Opportunities
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Author : Hai-Jew, Shalin
language : en
Publisher: IGI Global
Release Date : 2019-10-04
Profiling Target Learners For The Development Of Effective Learning Strategies Emerging Research And Opportunities written by Hai-Jew, Shalin and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-10-04 with Education categories.
Since the early days of formalized large-scale testing, there have been efforts to understand learners in order to provide better aligned learning opportunities and accommodations. What has been less explored has been how prospective and current target learners are profiled as target groups to adapt the learning to them, both statically (such as in pre-learning biographical profiling) and dynamically (on-the-fly as they interact with learning contents in online learning systems). This work takes more of a micro-scale and meso-scale approach, and these often involve both formal and informal means and creative teaching-and-learning accommodations. Profiling Target Learners for the Development of Effective Learning Strategies: Emerging Research and Opportunities is a critical scholarly resource that focuses on the practice of profiling prospective and current target learners through manual and computational means in order to better meet and improve their online and offline learning needs, as well as how those profiles influence the design, development, and provision of learning experiences. Featuring a wide range of topics such as diversity, curriculum design, and online learning, this book is ideal for educators, curriculum developers, instructional designers, principals, educational software developers, administrators, policymakers, academicians, researchers, and students.
Targeted Learning In Data Science
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Author : Mark J. van der Laan
language : en
Publisher: Springer
Release Date : 2018-03-28
Targeted Learning In Data Science written by Mark J. van der Laan and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-28 with Mathematics categories.
This textbook for graduate students in statistics, data science, and public health deals with the practical challenges that come with big, complex, and dynamic data. It presents a scientific roadmap to translate real-world data science applications into formal statistical estimation problems by using the general template of targeted maximum likelihood estimators. These targeted machine learning algorithms estimate quantities of interest while still providing valid inference. Targeted learning methods within data science area critical component for solving scientific problems in the modern age. The techniques can answer complex questions including optimal rules for assigning treatment based on longitudinal data with time-dependent confounding, as well as other estimands in dependent data structures, such as networks. Included in Targeted Learning in Data Science are demonstrations with soft ware packages and real data sets that present a case that targeted learning is crucial for the next generation of statisticians and data scientists. Th is book is a sequel to the first textbook on machine learning for causal inference, Targeted Learning, published in 2011. Mark van der Laan, PhD, is Jiann-Ping Hsu/Karl E. Peace Professor of Biostatistics and Statistics at UC Berkeley. His research interests include statistical methods in genomics, survival analysis, censored data, machine learning, semiparametric models, causal inference, and targeted learning. Dr. van der Laan received the 2004 Mortimer Spiegelman Award, the 2005 Van Dantzig Award, the 2005 COPSS Snedecor Award, the 2005 COPSS Presidential Award, and has graduated over 40 PhD students in biostatistics and statistics. Sherri Rose, PhD, is Associate Professor of Health Care Policy (Biostatistics) at Harvard Medical School. Her work is centered on developing and integrating innovative statistical approaches to advance human health. Dr. Rose’s methodological research focuses on nonparametric machine learning for causal inference and prediction. She co-leads the Health Policy Data Science Lab and currently serves as an associate editor for the Journal of the American Statistical Association and Biostatistics.