Описание: In this practical and comprehensive guide, author Martin Kleppmann helps you navigate this diverse landscape by examining the pros and cons of various technologies for processing and storing data.
Автор: Pradipta Maji; Sushmita Paul Название: Scalable Pattern Recognition Algorithms ISBN: 3319056298 ISBN-13(EAN): 9783319056296 Издательство: Springer Рейтинг: Цена: 18167.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book addresses the need for a unified framework describing how soft computing and machine learning techniques can be judiciously formulated and used in building efficient pattern recognition models.
Автор: Joachim Rossberg; Rickard Redler Название: Pro Scalable .NET 2.0 Application Designs ISBN: 1430211601 ISBN-13(EAN): 9781430211600 Издательство: Springer Рейтинг: Цена: 7126.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: * Uses the very latest version of Web Services Enhancements (WSE 3.0) when most competing titles still use the previous version (WSE 2.0 or WSE 1.0) and includes detailed consideration of the new Windows Server System and advises how to select the correct setup for your project.5
Описание: This book constitutes the refereed proceedings of the seven workshops co-located with the 14th International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2016, held in Sevilla, Spain, in June 2016.The 37 full papers presented were carefully reviewed and selected from 77 submissions.
Описание: The application and validation of agent-based models.- Methods, and technologies in a number of key application areas.- In day life and real world, energy and networks, human and trust, markets and bids, models and tools, negotiation and conversation, scalability and resources.
Автор: Bahaaldine Azarmi Название: Scalable Big Data Architecture ISBN: 1484213270 ISBN-13(EAN): 9781484213278 Издательство: Springer Рейтинг: Цена: 4186.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
This book highlights the different types of data architecture and illustrates the many possibilities hidden behind the term "Big Data", from the usage of No-SQL databases to the deployment of stream analytics architecture, machine learning, and governance.
Scalable Big Data Architecture covers real-world, concrete industry use cases that leverage complex distributed applications, which involve web applications, RESTful API, and high throughput of large amount of data stored in highly scalable No-SQL data stores such as Couchbase and Elasticsearch. This book demonstrates how data processing can be done at scale from the usage of NoSQL datastores to the combination of Big Data distribution.
When the data processing is too complex and involves different processing topology like long running jobs, stream processing, multiple data sources correlation, and machine learning, it's often necessary to delegate the load to Hadoop or Spark and use the No-SQL to serve processed data in real time.
This book shows you how to choose a relevant combination of big data technologies available within the Hadoop ecosystem. It focuses on processing long jobs, architecture, stream data patterns, log analysis, and real time analytics. Every pattern is illustrated with practical examples, which use the different open sourceprojects such as Logstash, Spark, Kafka, and so on.
Traditional data infrastructures are built for digesting and rendering data synthesis and analytics from large amount of data. This book helps you to understand why you should consider using machine learning algorithms early on in the project, before being overwhelmed by constraints imposed by dealing with the high throughput of Big data.
Scalable Big Data Architecture is for developers, data architects, and data scientists looking for a better understanding of how to choose the most relevant pattern for a Big Data project and which tools to integrate into that pattern.
Автор: Pradipta Maji; Sushmita Paul Название: Scalable Pattern Recognition Algorithms ISBN: 3319379658 ISBN-13(EAN): 9783319379654 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book addresses the need for a unified framework describing how soft computing and machine learning techniques can be judiciously formulated and used in building efficient pattern recognition models.
Автор: Vittal Prabhu; Soundar Kumara; Manjunath Kamath Название: Scalable Enterprise Systems ISBN: 1461350522 ISBN-13(EAN): 9781461350521 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Автор: Christoph Beierle; Alex Dekhtyar Название: Scalable Uncertainty Management ISBN: 3319235397 ISBN-13(EAN): 9783319235394 Издательство: Springer Рейтинг: Цена: 8944.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
The mysterious world of normal numbers.- Bayesian Networks.- Probabilistic Query Answering in the Bayesian Description Logic BEL.- The Complexity of Plate Probabilistic Models.- DL-Lite Bayesian Networks: A Tractable Probabilistic Graphical Model.- Probabilistic Models.- State Space Search with Stochastic Costs and Risk Aversion.- On the Impact of Junction-Tree Topology on Weighted Model Counting.- A System for Probabilistic Inductive Answer Set Programming.- Towards Large-Scale Probabilistic OBDA.- Reasoning over Linear Probabilistic Knowledge Bases with Priorities.- Intelligent Data Analytics.- Evenness-based reasoning with logical proportions applied to classification.- Multivariate Cluster-Based Discretization for Bayesian Network Structure Learning.- Modeling and Forecasting Time Series of Compositional Data: A Generalized Dirichlet Power Steady Model.- Linguistic and Graphical Explanation of a Cluster-based Data Structure.- Possibility Theory, Belief Functions and Transformations.- Probability-possibility transformations: Application to credal networks.- Planning in Partially Observable Domains with Fuzzy Epistemic States and Probabilistic Dynamics.- Propagation of Belief Functions in Singly-Connected Hybrid Directed Evidential Networks.- Uncertain logical gates in possibilistic networks. An application to human geography.- Argumentation.- Undercutting in argumentation systems.- Formalizing Explanatory Dialogues.- Towards a dual process cognitive model for argument evaluation.- Change in abstract bipolar argumentation systems.- On argumentation with purely defeasible rules.- Dealing with Inconsistency.- A possibilistic analysis of inconsistency.- First-Order Under-Approximations of Consistent Query Answers.- Using Rules of Thumb for Repairing Inconsistent Answer Set Program.- Applications.- Fuzzy XPath for the Automatic Search of Fuzzy Formulae Models.- ERBlox: Combining Matching Dependencies with Machine Learning for Entity Resolution.- Matching uncertain identities against sparse knowledge.
Автор: Lluis Godo; Andrea Pugliese Название: Scalable Uncertainty Management ISBN: 3642043879 ISBN-13(EAN): 9783642043871 Издательство: Springer Рейтинг: Цена: 10480.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This volume contains the papers presented at the Third International Conference on Scalable Uncertainty Management, SUM 2009, in Washington, DC, September 28-30, 2009.
Автор: Peter Mueller; Jiannong Cao; Cho-Li Wang Название: Scalable Information Systems ISBN: 3642104843 ISBN-13(EAN): 9783642104848 Издательство: Springer Рейтинг: Цена: 10480.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Includes the proceedings of the 4th International ICST Conference, INFOSCALE 2009, held in Hong Kong in June 2009. This title features papers that focus on various scalability issues and the approaches to tackle problems arising from the ever growing size and complexity of information.
Описание: The general problem addressed in this book is a large and important one: how to usefully deal with huge storehouses of complex information about real-world situations.
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