Автор: Trevor Hastie; Robert Tibshirani; Jerome Friedman Название: The Elements of Statistical Learning ISBN: 0387848576 ISBN-13(EAN): 9780387848570 Издательство: Springer Рейтинг: Цена: 10480.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This major new edition features many topics not covered in the original, including graphical models, random forests, and ensemble methods. As before, it covers the conceptual framework for statistical data in our rapidly expanding computerized world.
Автор: Scutari, Marco Название: The Pragmatic Programmer for Machine Learning ISBN: 0367263505 ISBN-13(EAN): 9780367263508 Издательство: Taylor&Francis Рейтинг: Цена: 11482.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Gives a holistic approach to machine learning and data science applications, from design to deployment and quality assurance, as an overarching cyclical process; Bridges machine learning and software engineering to build a shared set of best practices useful to both academia and the industry; Discusses deployment options for different types of models and data to help practitioners reason and make informed choices. Emphasizes the role of coding standards and software architecture alongside statistical rigor to implement reproducible and scalable machine learning modelsKey Features: A complete guide to software engineering for machine learning and data science applications, from choosing the right hardware to analysing algorithms and designing scalable architectures. Surveys the state of the art of the software and frameworks used to build and run machine learning applications, comparing and contrasting their trade-offs.
Comes with a complete case study in natural language understanding which illustrates the principles and the tools covered in the book. Code available from GitHub. Provides a multi-disciplinary view of how traditional software learning practices can be integrated with the workflows of domain experts and the unique characteristics of software in which data play a central role.
Автор: Gouse Baig Mohammad, S. Shitharth, Sachi Nandan Mohanty, Sirisha Potluri Название: Cloud Analytics for Industry 4.0 ISBN: 3110771497 ISBN-13(EAN): 9783110771497 Издательство: Walter de Gruyter Рейтинг: Цена: 28814.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides research on the state-of-the-art methods for data management in the fourth industrial revolution, with particular focus on cloud.based data analytics for digital manufacturing infrastructures. Innovative techniques and methods for secure, flexible and profi table cloud manufacturing will be gathered to present advanced and specialized research in the selected area.
Автор: Shi Название: Advances in Big Data Analytics ISBN: 9811636095 ISBN-13(EAN): 9789811636097 Издательство: Springer Рейтинг: Цена: 23757.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Today, big data affects countless aspects of our daily lives. This book provides a comprehensive and cutting-edge study on big data analytics, based on the research findings and applications developed by the author and his colleagues in related areas. It addresses the concepts of big data analytics and/or data science, multi-criteria optimization for learning, expert and rule-based data analysis, support vector machines for classification, feature selection, data stream analysis, learning analysis, sentiment analysis, link analysis, and evaluation analysis. The book also explores lessons learned in applying big data to business, engineering and healthcare. Lastly, it addresses the advanced topic of intelligence-quotient (IQ) tests for artificial intelligence. Since each aspect mentioned above concerns a specific domain of application, taken together, the algorithms, procedures, analysis and empirical studies presented here offer a general picture of big data developments. Accordingly, the book can not only serve as a textbook for graduates with a fundamental grasp of training in big data analytics, but can also show practitioners how to use the proposed techniques to deal with real-world big data problems.
Автор: C. Keith Harrison, Scott Bukstein Название: Sport Business Analytics ISBN: 1498761267 ISBN-13(EAN): 9781498761260 Издательство: Taylor&Francis Рейтинг: Цена: 17609.00 р. Наличие на складе: Поставка под заказ.
Описание:
Developing and implementing a systematic analytics strategy can result in a sustainable competitive advantage within the sport business industry. This timely and relevant book provides practical strategies to collect data and then convert that data into meaningful, value-added information and actionable insights. Its primary objective is to help sport business organizations utilize data-driven decision-making to generate optimal revenue from such areas as ticket sales and corporate partnerships. To that end, the book includes in-depth case studies from such leading sports organizations as the Orlando Magic, Tampa Bay Buccaneers, Duke University, and the Aspire Group.
The core purpose of sport business analytics is to convert raw data into information that enables sport business professionals to make strategic business decisions that result in improved company financial performance and a measurable and sustainable competitive advantage. Readers will learn about the role of big data and analytics in:
Ticket pricing
Season ticket member retention
Fan engagement
Sponsorship valuation
Customer relationship management
Digital marketing
Market research
Data visualization.
This book examines changes in the ticketing marketplace and spotlights innovative ticketing strategies used in various sport organizations. It shows how to engage fans with social media and digital analytics, presents techniques to analyze engagement and marketing strategies, and explains how to utilize analytics to leverage fan engagement to enhance revenue for sport organizations.
Filled with insightful case studies, this book benefits both sports business professionals and students. The concluding chapter on teaching sport analytics further enhances its value to academics.
Автор: Koitzsch Название: Pro Hadoop Data Analytics ISBN: 1484219090 ISBN-13(EAN): 9781484219096 Издательство: Springer Рейтинг: Цена: 5589.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Learn advanced analytical techniques and leverage existing toolkits to make your analytic applications more powerful, precise, and efficient. This book provides the right combination of architecture, design, and implementation information to create analytical systems which go beyond the basics of classification, clustering, and recommendation.In Pro Hadoop Data Analytics best practices are emphasized to ensure coherent, efficient development. A complete example system will be developed using standard third-party components which will consist of the toolkits, libraries, visualization and reporting code, as well as support glue to provide a working and extensible end-to-end system.The book emphasizes four important topics:The importance of end-to-end, flexible, configurable, high-performance data pipeline systems with analytical components as well as appropriate visualization results. Best practices and structured design principles. This will include strategic topics as well as the how to example portions.The importance of mix-and-match or hybrid systems, using different analytical components in one application to accomplish application goals. The hybrid approach will be prominent in the examples.Use of existing third-party libraries is key to effective development. Deep dive examples of the functionality of some of these toolkits will be showcased as you develop the example system.
What You'll Learn The what, why, and how of building big data analytic systems with the Hadoop ecosystemLibraries, toolkits, and algorithms to make development easier and more effectiveBest practices to use when building analytic systems with Hadoop, and metrics to measure performance and efficiency of components and systemsHow to connect to standard relational databases, noSQL data sources, and moreUseful case studies and example components which assist you in creating your own systems
Who This Book Is For
Software engineers, architects, and data scientists with an interest in the design and implementation of big data analytical systems using Hadoop, the Hadoop ecosystem, and other associated technologies.
Автор: Beard Название: Beginning SQL Server R Services ISBN: 1484222970 ISBN-13(EAN): 9781484222973 Издательство: Springer Рейтинг: Цена: 4191.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
Learn how to develop powerful data analytics applications quickly for SQL Server database administrators and developers. Organizations will be able to sift data and derive the business intelligence needed to drive business decisions and profit. The addition of R to SQL Server 2016 places a powerful analytical processor into an environment most developers are already comfortable with – Visual Studio. This book walks even the newest of users through the creation process of a powerful R-language tool set for use in analyzing and reporting on your data.As a SQL Server database administrator or developer, it is sometimes difficult to stay on the bleeding edge of technology. Microsoft’s addition of R to SQL Server 2016 is sure to be a game-changer, and the language will certainly become an integral part of future releases. R is in fact widely used today in statistical and related applications, and its use is only growing. Beginning SQL Server R Services helps you jump on board this important trend by providing good examples with detailed explanations of the WHY and not just the HOW.Walks you through setup and installation of SQL Server R Services.Explains the basics of working with R Tools for Visual Studio.Provides a road map to successfully creating custom R code.
What You Will Learn
Discover R’s role in the SQL Server 2016 hierarchy.Manage the components needed to run SQL Server R Services code.Run R-language analytics and queries inside the database.Create analytic solutions that run across multiple datasets.Gain in-depth knowledge of the R language itself.Implement custom SQL Server R Services solutions.
Who This Book Is For
Any level of database administrator or developer, but specifically it's for those developers with the need to develop powerful data analytics applications quickly. Seasoned R developers will appreciate the book for its robust learning pattern, using visual aids in combination with properties explanations and scenarios. Beginning SQL Server R Services is the perfect “new hire” gift for new database developers in any organization.
Автор: Wong Название: Big Data Analytics in Genomics ISBN: 3319412787 ISBN-13(EAN): 9783319412788 Издательство: Springer Рейтинг: Цена: 23757.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
This contributed volume explores the emerging intersection between big data analytics and genomics. Recent sequencing technologies have enabled high-throughput sequencing data generation for genomics resulting in several international projects which have led to massive genomic data accumulation at an unprecedented pace. To reveal novel genomic insights from this data within a reasonable time frame, traditional data analysis methods may not be sufficient or scalable, forcing the need for big data analytics to be developed for genomics. The computational methods addressed in the book are intended to tackle crucial biological questions using big data, and are appropriate for either newcomers or veterans in the field.
This volume offers thirteen peer-reviewed contributions, written by international leading experts from different regions, representing Argentina, Brazil, China, France, Germany, Hong Kong, India, Japan, Spain, and the USA. In particular, the book surveys three main areas: statistical analytics, computational analytics, and cancer genome analytics. Sample topics covered include: statistical methods for integrative analysis of genomic data, computation methods for protein function prediction, and perspectives on machine learning techniques in big data mining of cancer. Self-contained and suitable for graduate students, this book is also designed for bioinformaticians, computational biologists, and researchers in communities ranging from genomics, big data, molecular genetics, data mining, biostatistics, biomedical science, cancer research, medical research, and biology to machine learning and computer science. Readers will find this volume to be an essential read for appreciating the role of big data in genomics, making this an invaluable resource for stimulating further research on the topic.
Автор: Pyne Название: Big Data Analytics ISBN: 8132236262 ISBN-13(EAN): 9788132236269 Издательство: Springer Рейтинг: Цена: 15372.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book has a collection of articles written by Big Data experts to describe some of the cutting-edge methods and applications from their respective areas of interest, and provides the reader with a detailed overview of the field of Big Data Analytics as it is practiced today. The chapters cover technical aspects of key areas that generate and use Big Data such as management and finance; medicine and healthcare; genome, cytome and microbiome; graphs and networks; Internet of Things; Big Data standards; bench-marking of systems; and others. In addition to different applications, key algorithmic approaches such as graph partitioning, clustering and finite mixture modelling of high-dimensional data are also covered. The varied collection of themes in this volume introduces the reader to the richness of the emerging field of Big Data Analytics.
Автор: ElAtia Samira Название: Handbook of Data Mining and Learning Analytics ISBN: 1118998235 ISBN-13(EAN): 9781118998236 Издательство: Wiley Рейтинг: Цена: 17258.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Addresses the impacts of data mining on education and reviews applications in educational research teaching, and learning This book discusses the insights, challenges, issues, expectations, and practical implementation of data mining (DM) within educational mandates.
Автор: Simon Walkowiak Название: Big Data Analytics with R ISBN: 1786466457 ISBN-13(EAN): 9781786466457 Издательство: Неизвестно Рейтинг: Цена: 11217.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Utilize R to uncover hidden patterns in your Big Data About This Book Perform computational analyses on Big Data to generate meaningful results Get a practical knowledge of R programming language while working on Big Data platforms like Hadoop, Spark, H2O and SQL/NoSQL databases, Explore fast, streaming, and scalable data analysis with the most cutting-edge technologies in the market Who This Book Is For This book is intended for Data Analysts, Scientists, Data Engineers, Statisticians, Researchers, who want to integrate R with their current or future Big Data workflows. It is assumed that readers have some experience in data analysis and understanding of data management and algorithmic processing of large quantities of data, however they may lack specific skills related to R. What You Will Learn Learn about current state of Big Data processing using R programming language and its powerful statistical capabilities Deploy Big Data analytics platforms with selected Big Data tools supported by R in a cost-effective and time-saving manner Apply the R language to real-world Big Data problems on a multi-node Hadoop cluster, e.g. electricity consumption across various socio-demographic indicators and bike share scheme usage Explore the compatibility of R with Hadoop, Spark, SQL and NoSQL databases, and H2O platform In Detail Big Data analytics is the process of examining large and complex data sets that often exceed the computational capabilities. R is a leading programming language of data science, consisting of powerful functions to tackle all problems related to Big Data processing. The book will begin with a brief introduction to the Big Data world and its current industry standards. With introduction to the R language and presenting its development, structure, applications in real world, and its shortcomings. Book will progress towards revision of major R functions for data management and transformations. Readers will be introduce to Cloud based Big Data solutions (e.g. Amazon EC2 instances and Amazon RDS, Microsoft Azure and its HDInsight clusters) and also provide guidance on R connectivity with relational and non-relational databases such as MongoDB and HBase etc. It will further expand to include Big Data tools such as Apache Hadoop ecosystem, HDFS and MapReduce frameworks. Also other R compatible tools such as Apache Spark, its machine learning library Spark MLlib, as well as H2O. Style and approach This book will serve as a practical guide to tackling Big Data problems using R programming language and its statistical environment. Each section of the book will present you with concise and easy-to-follow steps on how to process, transform and analyse large data sets."
Автор: Madria Название: Big Data Analytics and Knowledge Discovery ISBN: 3319439456 ISBN-13(EAN): 9783319439457 Издательство: Springer Рейтинг: Цена: 8106.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The papers are organized in topical sections on Mining Big Data, Applications of Big Data Mining, Big Data Indexing and Searching, Big Data Learning and Security, Graph Databases and Data Warehousing, Data Intelligence and Technology.
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