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Big Data Analytics Methods, Ghavami Peter


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Автор: Ghavami Peter
Название:  Big Data Analytics Methods
ISBN: 9781547417957
Издательство: Walter de Gruyter
Классификация:




ISBN-10: 1547417951
Обложка/Формат: Paperback
Страницы: 254
Вес: 0.49 кг.
Дата издания: 16.12.2019
Серия: Economics/Business/Finance
Язык: English
Издание: 2nd edition
Иллюстрации: 14 tables, black and white; 88 illustrations, black and white
Размер: 239 x 170 x 18
Читательская аудитория: Professional and scholarly
Ключевые слова: Databases,Computer science, COMPUTERS / Data Processing,COMPUTERS / Databases / Data Mining,BUSINESS & ECONOMICS / Information Management,BUSINESS & ECONOMICS / Structural Adjustment
Подзаголовок: Analytics techniques in data mining, deep learning and natural language processing
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Поставляется из: Германии
Описание:

Big Data Analytics Methods unveils secrets to advanced analytics techniques ranging from machine learning, random forest classifiers, predictive modeling, cluster analysis, natural language processing (NLP), Kalman filtering and ensembles of models for optimal accuracy of analysis and prediction. More than 100 analytics techniques and methods provide big data professionals, business intelligence professionals and citizen data scientists insight on how to overcome challenges and avoid common pitfalls and traps in data analytics.

The book offers solutions and tips on handling missing data, noisy and dirty data, error reduction and boosting signal to reduce noise. It discusses data visualization, prediction, optimization, artificial intelligence, regression analysis, the Cox hazard model and many analytics using case examples with applications in the healthcare, transportation, retail, telecommunication, consulting, manufacturing, energy and financial services industries. This books state of the art treatment of advanced data analytics methods and important best practices will help readers succeed in data analytics.




Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems

Автор: Martin Kleppmann
Название: Designing Data-Intensive Applications: The Big Ideas Behind Reliable, Scalable, and Maintainable Systems
ISBN: 1449373321 ISBN-13(EAN): 9781449373320
Издательство: Wiley
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Цена: 7602.00 р.
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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.

People Analytics in the Era of Big Data: Changing the Way You Attract, Acquire, Develop, and Retain Talent

Автор: Isson Jean Paul
Название: People Analytics in the Era of Big Data: Changing the Way You Attract, Acquire, Develop, and Retain Talent
ISBN: 1119050782 ISBN-13(EAN): 9781119050780
Издательство: Wiley
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Цена: 6178.00 р.
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Описание: Apply predictive analytics throughout all stages of workforce management People Analytics in the Era of Big Data provides a blueprint for leveraging your talent pool through the use of data analytics.

Big Data Analytics

Автор: Pyne
Название: Big Data Analytics
ISBN: 8132236262 ISBN-13(EAN): 9788132236269
Издательство: Springer
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Цена: 15372.00 р.
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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.

Big Data Analytics and Knowledge Discovery

Автор: Madria
Название: Big Data Analytics and Knowledge Discovery
ISBN: 3319439456 ISBN-13(EAN): 9783319439457
Издательство: Springer
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Цена: 8106.00 р.
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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.

Big Data Analytics with R

Автор: Simon Walkowiak
Название: Big Data Analytics with R
ISBN: 1786466457 ISBN-13(EAN): 9781786466457
Издательство: Неизвестно
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Цена: 11217.00 р.
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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."

Big Data Analytics in Genomics

Автор: Wong
Название: Big Data Analytics in Genomics
ISBN: 3319412787 ISBN-13(EAN): 9783319412788
Издательство: Springer
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Цена: 23757.00 р.
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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.
Big data analytics with spark

Автор: Guller, Mohammed
Название: Big data analytics with spark
ISBN: 1484209656 ISBN-13(EAN): 9781484209653
Издательство: Springer
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Цена: 5309.00 р.
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Описание: Big Data Analytics with Spark is a step-by-step guide for learning Spark, which is an open-source fast and general-purpose cluster computing framework for large-scale data analysis.

Big Data Analytics for Sensor-Network Collected Intelligence

Автор: Hsu, Hui-Huang
Название: Big Data Analytics for Sensor-Network Collected Intelligence
ISBN: 0128093935 ISBN-13(EAN): 9780128093931
Издательство: Elsevier Science
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Цена: 15159.00 р.
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Описание:

Big Data Analytics for Sensor-Network Collected Intelligence explores state-of-the-art methods for using advanced ICT technologies to perform intelligent analysis on sensor collected data. The book shows how to develop systems that automatically detect natural and human-made events, how to examine people's behaviors, and how to unobtrusively provide better services.

It begins by exploring big data architecture and platforms, covering the cloud computing infrastructure and how data is stored and visualized. The book then explores how big data is processed and managed, the key security and privacy issues involved, and the approaches used to ensure data quality.

In addition, readers will find a thorough examination of big data analytics, analyzing statistical methods for data analytics and data mining, along with a detailed look at big data intelligence, ubiquitous and mobile computing, and designing intelligence system based on context and situation.

Indexing: The books of this series are submitted to EI-Compendex and SCOPUS


  • Contains contributions from noted scholars in computer science and electrical engineering from around the globe
  • Provides a broad overview of recent developments in sensor collected intelligence
  • Edited by a team comprised of leading thinkers in big data analytics
Cloud Infrastructures For Big Data Analytics

Автор: Raj & Chandra Deka
Название: Cloud Infrastructures For Big Data Analytics
ISBN: 1466658649 ISBN-13(EAN): 9781466658646
Издательство: Mare Nostrum (Eurospan)
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Цена: 50312.00 р.
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Описание: Clouds are being positioned as the next-generation consolidated, centralised, yet federated IT infrastructure for hosting all kinds of IT platforms and for deploying, maintaining, and managing a wider variety of personal, as well as professional, applications and services.Cloud Infrastructures for Big Data Analytics focuses exclusively on the topic of cloud-sponsored big data analytics for creating flexible and futuristic organisations. This book helps researchers and practitioners, as well as business entrepreneurs, to make informed decisions and consider appropriate action to simplify and streamline the arduous journey towards smarter enterprises.

Clustering Methods for Big Data Analytics

Автор: Olfa Nasraoui; Chiheb-Eddine Ben N`Cir
Название: Clustering Methods for Big Data Analytics
ISBN: 3030074196 ISBN-13(EAN): 9783030074197
Издательство: Springer
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Цена: 20962.00 р.
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Описание: This book highlights the state of the art and recent advances in Big Data clustering methods and their innovative applications in contemporary AI-driven systems. The book chapters discuss Deep Learning for Clustering, Blockchain data clustering, Cybersecurity applications such as insider threat detection, scalable distributed clustering methods for massive volumes of data; clustering Big Data Streams such as streams generated by the confluence of Internet of Things, digital and mobile health, human-robot interaction, and social networks; Spark-based Big Data clustering using Particle Swarm Optimization; and Tensor-based clustering for Web graphs, sensor streams, and social networks. The chapters in the book include a balanced coverage of big data clustering theory, methods, tools, frameworks, applications, representation, visualization, and clustering validation.

Clustering Methods for Big Data Analytics

Автор: Olfa Nasraoui; Chiheb-Eddine Ben N`Cir
Название: Clustering Methods for Big Data Analytics
ISBN: 3319978632 ISBN-13(EAN): 9783319978635
Издательство: Springer
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Цена: 20962.00 р.
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Описание: This book highlights the state of the art and recent advances in Big Data clustering methods and their innovative applications in contemporary AI-driven systems. The book chapters discuss Deep Learning for Clustering, Blockchain data clustering, Cybersecurity applications such as insider threat detection, scalable distributed clustering methods for massive volumes of data; clustering Big Data Streams such as streams generated by the confluence of Internet of Things, digital and mobile health, human-robot interaction, and social networks; Spark-based Big Data clustering using Particle Swarm Optimization; and Tensor-based clustering for Web graphs, sensor streams, and social networks. The chapters in the book include a balanced coverage of big data clustering theory, methods, tools, frameworks, applications, representation, visualization, and clustering validation.

Learning Spark: Lightning-Fast Big Data Analytics

Автор: Hamstra Mark, Zaharia Matei
Название: Learning Spark: Lightning-Fast Big Data Analytics
ISBN: 1449358624 ISBN-13(EAN): 9781449358624
Издательство: Wiley
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Цена: 5067.00 р.
Наличие на складе: Поставка под заказ.

Описание: Written by the developers of Spark, this book will have data scientists and engineers up and running in no time.


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