Small Summaries for Big Data, Graham Cormode, Ke Yi
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.
Описание: This new edition became necessary because in the frame of the system`s impressive evolution from an academic prototype to one of today`s most advanced core avionics, many elements were upgraded to their next technology generation and diverse new components complement the upgraded design.
Автор: Rashmi Agrawal; Marcin Paprzycki; Neha Gupta Название: Big data, iot, and machine learning ISBN: 036733674X ISBN-13(EAN): 9780367336745 Издательство: Taylor&Francis Рейтинг: Цена: 23734.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book discusses the Internet of Things (IoT) and Data Analytics from a technical, application, and business point of view. It describes essential technical knowledge, building blocks, processes, design principles, and implementation of big data tools and machine learning techniques and applications for IoT projects.
Описание: This book aims to provide some insights into recently developed bio-inspired algorithms within recent emerging trends of fog computing, sentiment analysis, and data streaming as well as to provide a more comprehensive approach to the big data management from pre-processing to analytics to visualization phases.
Автор: Cerquitelli Tania, Quercia Daniele, Pasquale Frank Название: Transparent Data Mining for Big and Small Data ISBN: 331985299X ISBN-13(EAN): 9783319852997 Издательство: Springer Рейтинг: Цена: 19564.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book focuses on new and emerging data mining solutions that offer a greater level of transparency than existing solutions.
Описание: As organizations continue to develop, there is an increasing need for technological methods that can keep up with the rising amount of data and information that is being generated. Machine learning is a tool that has become powerful due to its ability to analyze large amounts of data quickly. Machine learning is one of many technological advancements that is being implemented into a multitude of specialized fields. An extensive study on the execution of these advancements within professional industries is necessary.
Advanced Multi-Industry Applications of Big Data Clustering and Machine Learning is an essential reference source that synthesizes the analytic principles of clustering and machine learning to big data and provides an interface between the main disciplines of engineering/technology and the organizational, administrative, and planning abilities of management. Featuring research on topics such as project management, contextual data modeling, and business information systems, this book is ideally designed for engineers, economists, finance officers, marketers, decision makers, business professionals, industry practitioners, academicians, students, and researchers seeking coverage on the implementation of big data and machine learning within specific professional fields.
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: Cerquitelli, Tania, Quercia, Daniele, Pasquale, Frank (Eds.) Название: Transparent data mining for big and small data. ISBN: 3319540238 ISBN-13(EAN): 9783319540238 Издательство: Springer Рейтинг: Цена: 16769.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book focuses on new and emerging data mining solutions that offer a greater level of transparency than existing solutions.
Описание: 1. Introduction.- 2. Data Engineering and Exploratory Data Analysis Techniques.- 3. Agricultural Economy and ML Models.- 4. Commodity Markets - Machine Learning Techniques.- 5. Weather Patterns and Machine Learning.- 6. Agriculture Employment and the Role of AI in improving Productivity.- 7. Role of Government and the AI Readiness.- 8. Future.
Автор: ?loi Boss? And Basel Solaiman Название: Information Fusion And Analytics For Big Data And Iot ISBN: 1630810878 ISBN-13(EAN): 9781630810870 Издательство: Artech House Рейтинг: Цена: 26426.00 р. Наличие на складе: Нет в наличии.
Описание: The Internet of Things (IoT) and Big Data are hot topics in the world of intelligence operations and information gathering. This first-of-its-kind volume reveals the benefits of addressing these topics with the integration of Fusion of Information and Analytics Technologies (FIAT). The book explains how FIAT is materialized into decision support systems that are capable of supporting the prognosis, diagnosis, and prescriptive tasks within complex systems and organizations.This unique resource offers keen insight into how complex systems emerge from the interrelation of social and cognitive information, cyber and physical worlds, and the various models of decision-making and situational awareness. Practitioners also discover the central notions of analytics and information fusion. Moreover the book introduces propos such as integration through a FIAT computational model and applications at the systems level. This book concludes with a list of prospective research activities that can contribute towards the required FIAT integration for critical application domains such as: energy, health, transport and defense and security.
Автор: Witold Pedrycz; Shyi-Ming Chen Название: Information Granularity, Big Data, and Computational Intelligence ISBN: 331938161X ISBN-13(EAN): 9783319381619 Издательство: Springer Рейтинг: Цена: 18284.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Nearest Neighbor Queries on Big Data.- Information Mining for Big Information.- Information Granules Problem: An Efficient Solution of Real-Time Fuzzy Regression Analysis.- How to Understand Connections Based on Big Data: From Cliques to Flexible Granules.- Maintain 'Omics: When e-Maintenance Enters the Big Data Era.- Incrementally Mining Frequent Patterns for Large Database.- Improved Latent Semantic Indexing-based Data Mining Methods and An Application to Big.- The Property of Different Granule and Granular Methods Based on Quotient Space.- Towards An Optimal Task-Driven Information Granulation.- Unified Framework for Construction of Rule Based Classification Systems.- Multi-granular Evaluation Model through Fuzzy Random Regression to Improve Information.- Building Fuzzy Robust Regression Model Based on Granularity and Possibility Distribution.- The Role of Cloud Computing Architectures in Big Data.- Big Data Storage Techniques for Spatial Databases: Implications of Big Data Architecture on Spatial Query Processing.- The Web KnowARR Framework: Orchestrating Computational Intelligence with Graph Databases.- Customer Relationship Management and Big Data Mining.- Performance Competition for ISCIFCM and Application of Computational Intelligence on Analysis of Air Quality Monitoring Big Data.-PEI Models under Uncontrolled Circumstances.- Rough Set Model based Knowledge Acquisition of Market Movements from Economic Data.- Deep Neural Network Modeling for Big Data Weather Forecast.- Current Knowledge and Future Challenge for Visibility Forecasting by Computational Intelligence.- Application of Computational Intelligence on Analysis of Air Quality Monitoring Big Data.
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