High-dimensional data analysis with low-dimensional models, Wright, John (columbia University, New York) Ma, Yi (university Of California, Berkeley)
Автор: Currell Graham Название: Scientific Data Analysis ISBN: 0198712545 ISBN-13(EAN): 9780198712541 Издательство: Oxford Academ Рейтинг: Цена: 7602.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Drawing on the author`s extensive experience of supporting students undertaking projects, Scientific Data Analysis is a guide for any science undergraduate or beginning graduate who needs to analyse their own data, and wants a clear, step-by-step description of how to carry out their analysis in a robust, error-free way.
Автор: Edmond Jennifer, Mandal Anthony, Horsley Nicola Название: The Trouble with Big Data: How Datafication Displaces Cultural Practices ISBN: 1350239623 ISBN-13(EAN): 9781350239623 Издательство: Bloomsbury Academic Рейтинг: Цена: 27588.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This open access book explores the challenges society faces with big data, through the lens of culture rather than social, political or economic trends, as demonstrated in the words we use, the values that underpin our interactions, and the biases and assumptions that drive us. Focusing on areas such as data and language, data and sensemaking, data and power, data and invisibility, and big data aggregation, it demonstrates that humanities research, focussing on cultural rather than social, political or economic frames of reference for viewing technology, resists mass datafication for a reason, and that those very reasons can be instructive for the critical observation of big data research and innovation.
The eBook editions of this book are available open access under a CC BY-NC-ND 4.0 licence on bloomsburycollections.com. Open access was funded by Trinity College Dublin, DARIAH-EU and the European Commission.
Автор: Gine, Evarist Nickl, Richard (university Of Cambridge) Название: Mathematical foundations of infinite-dimensional statistical models ISBN: 110899413X ISBN-13(EAN): 9781108994132 Издательство: Cambridge Academ Рейтинг: Цена: 7286.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: High-dimensional and nonparametric statistical models are ubiquitous in modern data science. This book develops a mathematically coherent and objective approach to statistical inference in such models, with a focus on function estimation problems arising from random samples or from Gaussian regression/signal in white noise problems.
Описание: It draws attention to the deficiencies of standard statistical tools when used in the high-dimensional setting, and introduces the basic concepts and major results related to spectral statistics and random matrix theory under high-dimensional asymptotics in an understandable and reader-friendly way.
Описание: This textbook provides a step-by-step introduction to the tools and principles of high-dimensional statistics. The book covers the theory and practice of high-dimensional linear regression, graphical models, and inference, ensuring readers have a smooth start in the field. It also offers suggestions for further reading.
Автор: Thomas A. Runkler Название: Data Analytics ISBN: 3658297786 ISBN-13(EAN): 9783658297787 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book is a comprehensive introduction to the methods and algorithms of modern data analytics. It provides a sound mathematical basis, discusses advantages and drawbacks of different approaches, and enables the reader to design and implement data analytics solutions for real-world applications.
Автор: International Atomic Energy Agency Название: Benchmark analysis of numerical models for tsunami simulation ISBN: 9201284217 ISBN-13(EAN): 9789201284211 Издательство: Mare Nostrum (Eurospan) Рейтинг: Цена: 2633.00 р. Наличие на складе: Нет в наличии.
Описание: In recent years there has been an evolution in numerical models used to compute tsunami propagation and run-up. Many models currently available offer a wide array of choices to the users. In parallel with the development of such numerical models, it is important that the user only applies the verified and validated numerical models that have undergone a benchmark analysis. This publication provides information and benchmark problems to enable engineers and regulators to select the most appropriate tsunami analysis software and modelling for the evaluation of tsunami hazards for nuclear installations to ensure their safety against those events. In addition, the benchmark problems will enable such users to become familiar with the limitations of the tsunami analysis modelling available in research and commercial software.
Автор: Scott Duxbury Название: Longitudinal Network Models ISBN: 1071857738 ISBN-13(EAN): 9781071857731 Издательство: Sage Publications Рейтинг: Цена: 5859.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Although longitudinal social network data are increasingly collected, there are few guides on how to navigate the range of available tools for longitudinal network analysis. The applied social scientist is left to wonder: Which model is most appropriate for my data? How should I get started with this modeling strategy? And how do I know if my model is any good? This book answers these questions. Author Scott Duxbury assumes that the reader is familiar with network measurement, description, and notation, and is versed in regression analysis, but is likely unfamiliar with statistical network methods. The goal of the book is to guide readers towards choosing, applying, assessing, and interpreting a longitudinal network model, and each chapter is organized with a specific data structure or research question in mind. A companion website includes data and R code to replicate the examples in the book.
Автор: Tim Roughgarden Название: Beyond the Worst-Case Analysis of Algorithms ISBN: 1108494315 ISBN-13(EAN): 9781108494311 Издательство: Cambridge Academ Рейтинг: Цена: 9187.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Understanding when and why algorithms work is a fundamental challenge. For problems ranging from clustering to linear programming to neural networks there are significant gaps between empirical performance and prediction based on traditional worst-case analysis. The book introduces exciting new methods for assessing algorithm performance.
Автор: Pennington Diane Название: Social Tagging for Linking Data Across Environments ISBN: 1783303387 ISBN-13(EAN): 9781783303380 Издательство: Facet Рейтинг: Цена: 16368.00 р. Наличие на складе: Нет в наличии.
Описание: This book, representing researchers and practitioners across different information professions, will explore how social tags can link content across a variety of environments.
Описание: Fake news may have reached new notoriety since the 2016 US election, but it has been around a long time. In All That`s Not Fit to Print, Amy Affelt offers tools and techniques for spotting fake news and discusses best practices for finding high quality sources, information, and data.
Автор: Subasi, Abdulhamit Название: Practical Machine Learning For Data Analysis Using Python ISBN: 0128213795 ISBN-13(EAN): 9780128213797 Издательство: Elsevier Science Рейтинг: Цена: 16505.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Practical Machine Learning for Data Analysis Using Python is a problem solver's guide for creating real-world intelligent systems. It provides a comprehensive approach with concepts, practices, hands-on examples, and sample code. The book teaches readers the vital skills required to understand and solve different problems with machine learning. It teaches machine learning techniques necessary to become a successful practitioner, through the presentation of real-world case studies in Python machine learning ecosystems. The book also focuses on building a foundation of machine learning knowledge to solve different real-world case studies across various fields, including biomedical signal analysis, healthcare, security, economics, and finance. Moreover, it covers a wide range of machine learning models, including regression, classification, and forecasting. The goal of the book is to help a broad range of readers, including IT professionals, analysts, developers, data scientists, engineers, and graduate students, to solve their own real-world problems.
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