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: 29887.00 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: Mittal Название: Big Data Processing Using Spark in Cloud ISBN: 9811305498 ISBN-13(EAN): 9789811305498 Издательство: Springer Рейтинг: Цена: 12196.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The book describes the emergence of big data technologies and the role of Spark in the entire big data stack.
Автор: Bairong Shen Название: Healthcare and Big Data Management ISBN: 9811060401 ISBN-13(EAN): 9789811060403 Издательство: Springer Рейтинг: Цена: 18294.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The book addresses the interplay of healthcare and big data management. Thanks to major advances in big data technologies and precision medicine, healthcare is now becoming the new frontier for both scientific research and economic development. This volume covers a range of aspects, including: big data management for healthcare;
Автор: Jemielniak, Dariusz (full Professor Of Management, Full Professor Of Management, Kozminski University) Название: Thick big data ISBN: 0198839715 ISBN-13(EAN): 9780198839712 Издательство: Oxford Academ Рейтинг: Цена: 6454.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Thick Big Data presents the available arsenal of new methods and tools for studying society both quantitatively and qualitatively, opening ground for the social sciences to take the lead in analysing digital behaviour. These tools are critical for students and researchers in the social sciences to successfully build mixed-methods approaches.
Автор: Karen L Webber Название: Big Data on Campus ISBN: 1421439034 ISBN-13(EAN): 9781421439037 Издательство: Wiley Рейтинг: Цена: 5861.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Webber, Henry Y. Zheng, Ying Zhou
Автор: Graham Cormode, Ke Yi Название: Small Summaries for Big Data ISBN: 1108477445 ISBN-13(EAN): 9781108477444 Издательство: Cambridge Academ Рейтинг: Цена: 7602.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The massive volume of data generated in modern applications requires the ability to build compact summaries of datasets. This introduction aimed at students and practitioners covers algorithms to describe massive data sets from simple sums to advanced probabilistic structures, with applications in big data, data science, and machine learning.
Название: Application of big data and business analytics ISBN: 1800438850 ISBN-13(EAN): 9781800438859 Издательство: Emerald Рейтинг: Цена: 16870.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Application of Big Data and Business Analytics uses advanced analytic tools to explore the solutions to problems in society, environment and industry. The chapters within bring together researchers, engineers and practitioners, encompassing a wide and diverse set of topics in almost every field.
With the increase in the availability of data, analytics has now become a major element in both the top line and the bottom line of any organization. With this in mind, Application of Big Data and Business Analytics brings together researchers, engineers and practitioners, encompassing a wide and diverse set of topics in almost every field.
The primary target audience of this book includes researchers, academicians and data scientists from a variety of disciplines interested in analyzing and application of big data analytics. However, this work will also be of general interest to postgraduates and undergraduates pursuing advanced study in big data.
Автор: Pietsch, Wolfgang Название: Big data ISBN: 110870669X ISBN-13(EAN): 9781108706698 Издательство: Cambridge Academ Рейтинг: Цена: 2851.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Big Data and methods for analyzing large data sets such as machine learning have deeply transformed scientific practice in many fields. This Element defends an inductivist view of big data research and argues that the type of induction employed by the most successful big data algorithms is variational induction in the tradition of Mill`s methods.
Автор: Jemielniak Dariusz Название: Thick Big Data: Doing Digital Social Sciences ISBN: 0198839707 ISBN-13(EAN): 9780198839705 Издательство: Oxford Academ Рейтинг: Цена: 24025.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Thick Big Data presents the available arsenal of new methods and tools for studying society both quantitatively and qualitatively, opening ground for the social sciences to take the lead in analysing digital behaviour. These tools are critical for students and researchers in the social sciences to successfully build mixed-methods approaches.
Автор: Sharma Rohit, Sharma Dilip Kumar, Bhatt Dhowmya Название: Big Data Analysis for Green Computing: Concepts and Applications ISBN: 0367442302 ISBN-13(EAN): 9780367442309 Издательство: Taylor&Francis Рейтинг: Цена: 26796.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book focuses on big data in business intelligence, data management, machine learning, cloud computing, and smart cities. It also provides an interdisciplinary platform to present and discuss recent innovations, trends, and concerns in the fields of big data and analytics.
Автор: Licastro Amanda, Miller Benjamin Название: Composition and Big Data ISBN: 0822946742 ISBN-13(EAN): 9780822946748 Издательство: World Scientific Publishing Цена: 12415.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book interprets and implements the drive toward data in diverse ways.
Автор: Johnson I. Agbinya Название: Applied Data Analytics - Principles and Applications ISBN: 8770220964 ISBN-13(EAN): 9788770220965 Издательство: Taylor&Francis Рейтинг: Цена: 14851.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The emergence of huge amounts of data which require analysis and in some cases real-time processing has forced exploration into fast algorithms for handling very lage data sizes. Analysis of x-ray images in medical applications, cyber security data, crime data, telecommunications and stock market data, health records and business analytics data are but a few areas of interest. Applications and platforms including R, RapidMiner and Weka provide the basis for analysis, often used by practitioners who pay little to no attention to the underlying mathematics and processes impacting the data. This often leads to an inability to explain results or correct mistakes, or to spot errors.
Applied Data Analytics - Principles and Applications seeks to bridge this missing gap by providing some of the most sought after techniques in big data analytics. Establishing strong foundations in these topics provides practical ease when big data analyses are undertaken using the widely available open source and commercially orientated computation platforms, languages and visualisation systems. The book, when combined with such platforms, provides a complete set of tools required to handle big data and can lead to fast implementations and applications.
The book contains a mixture of machine learning foundations, deep learning, artificial intelligence, statistics and evolutionary learning mathematics written from the usage point of view with rich explanations on what the concepts mean. The author has thus avoided the complexities often associated with these concepts when found in research papers. The tutorial nature of the book and the applications provided are some of the reasons why the book is suitable for undergraduate, postgraduate and big data analytics enthusiasts.
This text should ease the fear of mathematics often associated with practical data analytics and support rapid applications in artificial intelligence, environmental sensor data modelling and analysis, health informatics, business data analytics, data from Internet of Things and deep learning applications.
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