Learning From Data
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Learning From Data
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Author : Yaser S. Abu-Mostafa
language : en
Publisher:
Release Date : 2012-01-01
Learning From Data written by Yaser S. Abu-Mostafa and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-01-01 with Machine learning categories.
Learning From Data
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Author : Vladimir Cherkassky
language : en
Publisher: John Wiley & Sons
Release Date : 2007-09-10
Learning From Data written by Vladimir Cherkassky and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-09-10 with Computers categories.
An interdisciplinary framework for learning methodologies—covering statistics, neural networks, and fuzzy logic, this book provides a unified treatment of the principles and methods for learning dependencies from data. It establishes a general conceptual framework in which various learning methods from statistics, neural networks, and fuzzy logic can be applied—showing that a few fundamental principles underlie most new methods being proposed today in statistics, engineering, and computer science. Complete with over one hundred illustrations, case studies, and examples making this an invaluable text.
Learning From Data
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Author : Arthur Glenberg
language : en
Publisher: Routledge
Release Date : 2007-08-09
Learning From Data written by Arthur Glenberg and has been published by Routledge this book supported file pdf, txt, epub, kindle and other format this book has been release on 2007-08-09 with Education categories.
Learning from Data focuses on how to interpret psychological data and statistical results. The authors review the basics of statistical reasoning to helpstudents better understand relevant data that affecttheir everyday lives. Numerous examples based on current research and events are featured throughout.To facilitate learning, authors Glenberg and Andrzejewski: Devote extra attention to explaining the more difficult concepts and the logic behind them Use repetition to enhance students’ memories with multiple examples, reintroductions of the major concepts, and a focus on these concepts in the problems Employ a six-step procedure for describing all statistical tests from the simplest to the most complex Provide end-of-chapter tables to summarize the hypothesis testing procedures introduced Emphasizes how to choose the best procedure in the examples, problems and endpapers Focus on power with a separate chapter and power analyses procedures in each chapter Provide detailed explanations of factorial designs, interactions, and ANOVA to help students understand the statistics used in professional journal articles. The third edition has a user-friendly approach: Designed to be used seamlessly with Excel, all of the in-text analyses are conducted in Excel, while the book’s downloadable resources contain files for conducting analyses in Excel, as well as text files that can be analyzed in SPSS, SAS, and Systat Two large, real data sets integrated throughout illustrate important concepts Many new end-of-chapter problems (definitions, computational, and reasoning) and many more on the companion CD Online Instructor’s Resources includes answers to all the exercises in the book and multiple-choice test questions with answers Boxed media reports illustrate key concepts and their relevance to realworld issues The inclusion of effect size in all discussions of power accurately reflects the contemporary issues of power, effect size, and significance. Learning From Data, Third Edition is intended as a text for undergraduate or beginning graduate statistics courses in psychology, education, and other applied social and health sciences.
Learning From Data
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Author : IntroBooks Team
language : en
Publisher: IntroBooks
Release Date :
Learning From Data written by IntroBooks Team and has been published by IntroBooks this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
Learning from Data is the concept which has developed recently. Data is a concept which is raw in nature and it has been given meaning only after compilation and currently, after globalization. The amount of data in all the sectors have grown enormously. Learning from Data is a very popular concept now as companies are saving data only to extract and make analysis out of the same on which various other factors are dependent. The other factors are majorly competitive basis and help big tier companies to study the market and grow even more in the present competitive era. With so much data around, another important aspect is the protection of data. To make use of data, the next major factor is its protection as since the competition exists in all fields; the data field is no exception. Data is the current trending concept all over the globe and research over the same will undoubtedly fetch more of analysis.
Learning From Data Streams In Dynamic Environments
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Author : Moamar Sayed-Mouchaweh
language : en
Publisher: Springer
Release Date : 2015-12-10
Learning From Data Streams In Dynamic Environments written by Moamar Sayed-Mouchaweh and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-12-10 with Technology & Engineering categories.
This book addresses the problems of modeling, prediction, classification, data understanding and processing in non-stationary and unpredictable environments. It presents major and well-known methods and approaches for the design of systems able to learn and to fully adapt its structure and to adjust its parameters according to the changes in their environments. Also presents the problem of learning in non-stationary environments, its interests, its applications and challenges and studies the complementarities and the links between the different methods and techniques of learning in evolving and non-stationary environments.
Inference And Learning From Data Volume 3
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Author : Ali H. Sayed
language : en
Publisher: Cambridge University Press
Release Date : 2022-12-22
Inference And Learning From Data Volume 3 written by Ali H. Sayed 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 2022-12-22 with Technology & Engineering categories.
This extraordinary three-volume work, written in an engaging and rigorous style by a world authority in the field, provides an accessible, comprehensive introduction to the full spectrum of mathematical and statistical techniques underpinning contemporary methods in data-driven learning and inference. This final volume, Learning, builds on the foundational topics established in volume I to provide a thorough introduction to learning methods, addressing techniques such as least-squares methods, regularization, online learning, kernel methods, feedforward and recurrent neural networks, meta-learning, and adversarial attacks. A consistent structure and pedagogy is employed throughout this volume to reinforce student understanding, with over 350 end-of-chapter problems (including complete solutions for instructors), 280 figures, 100 solved examples, datasets and downloadable Matlab code. Supported by sister volumes Foundations and Inference, and unique in its scale and depth, this textbook sequence is ideal for early-career researchers and graduate students across many courses in signal processing, machine learning, data and inference.
Inference And Learning From Data Volume 1
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Author : Ali H. Sayed
language : en
Publisher: Cambridge University Press
Release Date : 2022-12-22
Inference And Learning From Data Volume 1 written by Ali H. Sayed 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 2022-12-22 with Technology & Engineering categories.
This extraordinary three-volume work, written in an engaging and rigorous style by a world authority in the field, provides an accessible, comprehensive introduction to the full spectrum of mathematical and statistical techniques underpinning contemporary methods in data-driven learning and inference. This first volume, Foundations, introduces core topics in inference and learning, such as matrix theory, linear algebra, random variables, convex optimization and stochastic optimization, and prepares students for studying their practical application in later volumes. A consistent structure and pedagogy is employed throughout this volume to reinforce student understanding, with over 600 end-of-chapter problems (including solutions for instructors), 100 figures, 180 solved examples, datasets and downloadable Matlab code. Supported by sister volumes Inference and Learning, and unique in its scale and depth, this textbook sequence is ideal for early-career researchers and graduate students across many courses in signal processing, machine learning, statistical analysis, data science and inference.
Learning From Data Streams
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Author : João Gama
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-09-20
Learning From Data Streams written by João Gama 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 2007-09-20 with Computers categories.
Sensor networks consist of distributed autonomous devices that cooperatively monitor an environment. Sensors are equipped with capacities to store information in memory, process this information and communicate with their neighbors. Processing data streams generated from wireless sensor networks has raised new research challenges over the last few years due to the huge numbers of data streams to be managed continuously and at a very high rate. The book provides the reader with a comprehensive overview of stream data processing, including famous prototype implementations like the Nile system and the TinyOS operating system. The set of chapters covers the state-of-art in data stream mining approaches using clustering, predictive learning, and tensor analysis techniques, and applying them to applications in security, the natural sciences, and education. This research monograph delivers to researchers and graduate students the state of the art in data stream processing in sensor networks. The huge bibliography offers an excellent starting point for further reading and future research.
Utility Based Learning From Data
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Author : Craig Friedman
language : en
Publisher: CRC Press
Release Date : 2016-04-19
Utility Based Learning From Data written by Craig Friedman and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-04-19 with Business & Economics categories.
Utility-Based Learning from Data provides a pedagogical, self-contained discussion of probability estimation methods via a coherent approach from the viewpoint of a decision maker who acts in an uncertain environment. This approach is motivated by the idea that probabilistic models are usually not learned for their own sake; rather, they are used t
Statistics
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Author : Alan Agresti
language : en
Publisher:
Release Date : 2013
Statistics written by Alan Agresti and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013 with categories.