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Big Data Analytics,33, Govindaraju,Venu


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Цена: 205490.00T
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Автор: Govindaraju,Venu
Название:  Big Data Analytics,33
ISBN: 9780444634924
Издательство: Elsevier Science
Классификация:
ISBN-10: 0444634924
Обложка/Формат: Hardback
Страницы: 390
Вес: 0.76 кг.
Дата издания: 07.07.2015
Серия: Handbook of statistics
Язык: English
Размер: 160 x 239 x 22
Основная тема: Serial product
Ссылка на Издательство: Link
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Поставляется из: Европейский союз

Using R at the Bench: Step-By-Step Data Analytics for Biologists

Автор: Bremer Martina, Doerge Rebecca W.
Название: Using R at the Bench: Step-By-Step Data Analytics for Biologists
ISBN: 1621821129 ISBN-13(EAN): 9781621821120
Издательство: Неизвестно
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Цена: 102690.00 T
Наличие на складе: Невозможна поставка.
Описание: Using R at the Bench: Step-by-Step Data Analytics for Biologists is a convenient bench-side handbook for biologists, designed as a handy reference guide for elementary and intermediate statistical analyses using the free/public software package known as R. The expectations for biologists to
have a more complete understanding of statistics are growing rapidly. New technologies and new areas of science, such as microarrays, next-generation sequencing, and proteomics, have dramatically increased the need for quantitative reasoning among biologists when designing experiments and
interpreting results. Even the most routine informatics tools rely on statistical assumptions and methods that need to be appreciated if the scientific results are to be correct, understood, and exploited fully.

Although the original Statistics at the Bench is still available for sale and has all examples in Excel, this new book uses the same text and examples in R. A new chapter introduces the basics of R: where to download, how to get started, and some basic commands and resources. There is also a new
chapter that explains how to analyze next-generation sequencing data using R (specifically, RNA-Seq). R is powerful statistical software with many specialized packages for biological applications and Using R at the Bench: Step-by-Step Data Analytics for Biologists is an excellent resource for those
biologists who want to learn R. This handbook for working scientists provides a simple refresher for those who have forgotten what they once knew and an overview for those wishing to use more quantitative reasoning in their research. Statistical methods, as well as guidelines for the interpretation
of results, are explained using simple examples. Throughout the book, examples are accompanied by detailed R commands for easy reference.

Quantitative Trading

Автор: Guo, Xin , Lai, Tze Leung , Shek, Howard , Wong
Название: Quantitative Trading
ISBN: 0367871815 ISBN-13(EAN): 9780367871819
Издательство: Taylor&Francis
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Цена: 63280.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The first part of this book discusses institutions and mechanisms of algorithmic trading, market microstructure, high-frequency data and stylized facts, time and event aggregation, order book dynamics, trading strategies and algorithms, transaction costs, market impact and execution strategies, risk analysis, and management. The second part cove

Exploratory Data Analytics for Healthcare

Автор: Kumar R. Lakshmana, Indrakumari R., Balamurugan B.
Название: Exploratory Data Analytics for Healthcare
ISBN: 0367506912 ISBN-13(EAN): 9780367506919
Издательство: Taylor&Francis
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Цена: 148010.00 T
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Описание: Exploratory data analysis helps to recognize natural patterns hidden in the data. This book describes the tools for hypothesis generation by visualizing data through graphical representation and provides insight into advanced analytics concepts in an easy way.

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: 158380.00 T
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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 and Knowledge Discovery

Автор: Wrembel
Название: Big Data Analytics and Knowledge Discovery
ISBN: 3031398300 ISBN-13(EAN): 9783031398308
Издательство: Springer
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Цена: 61480.00 T
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Описание: This book constitutes the proceedings of the 25th International Conference on Big Data Analytics and Knowledge Discovery, DaWaK 2023, which took place in Penang, Malaysia, during August 29-30, 2023. The 18 full papers presented together with 19 short papers were carefully reviewed and selected from a total of 83 submissions. They were organized in topical sections as follows: Data quality; advanced analytics and pattern discovery; machine learning; deep learning; and data management.

Big Data Analytics

Автор: Pyne
Название: Big Data Analytics
ISBN: 8132236262 ISBN-13(EAN): 9788132236269
Издательство: Springer
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Цена: 102480.00 T
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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: Wrembel
Название: Big Data Analytics and Knowledge Discovery
ISBN: 3031126696 ISBN-13(EAN): 9783031126697
Издательство: Springer
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Цена: 65210.00 T
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Описание: This volume LNCS 13428 constitutes the papers of the 24 th International Conference on Big Data Analytics and Knowledge Discovery, held in August 2022 in Vienna, Austria. The 12 full papers presented together with 12 short papers in this volume were carefully reviewed and selected from a total of 57 submissions. The papers reflect a wide range of topics in the field of data integration, data warehousing, data analytics, and recently big data analytics, in a broad sense. The main objectives of this event are to explore, disseminate, and exchange knowledge in these fields.

Big Data Analytics

Автор: Matter, Ulrich
Название: Big Data Analytics
ISBN: 1032458143 ISBN-13(EAN): 9781032458144
Издательство: Taylor&Francis
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Цена: 42870.00 T
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Data Science and Big Data Analytics in Smart Environments

Автор: Chinnici, Marta ; Pop, Florin ; Negru, Catalin
Название: Data Science and Big Data Analytics in Smart Environments
ISBN: 0367776030 ISBN-13(EAN): 9780367776039
Издательство: Taylor&Francis
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Цена: 59190.00 T
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Data Science Foundations

Название: Data Science Foundations
ISBN: 1498763936 ISBN-13(EAN): 9781498763936
Издательство: Taylor&Francis
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Цена: 91860.00 T
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Handbook of Big Data Analytics

Автор: Wolfgang Karl H?rdle; Henry Horng-Shing Lu; Xiaoto
Название: Handbook of Big Data Analytics
ISBN: 3319182838 ISBN-13(EAN): 9783319182834
Издательство: Springer
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Цена: 260870.00 T
Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Addressing a broad range of big data analytics in cross-disciplinary applications, this essential handbook focuses on the statistical prospects offered by recent developments in this field. To do so, it covers statistical methods for high-dimensional problems, algorithmic designs, computation tools, analysis flows and the software-hardware co-designs that are needed to support insightful discoveries from big data. The book is primarily intended for statisticians, computer experts, engineers and application developers interested in using big data analytics with statistics. Readers should have a solid background in statistics and computer science.

Big Data Analytics for Smart Urban Systems

Автор: Pourroostaei Ardakani
Название: Big Data Analytics for Smart Urban Systems
ISBN: 9819955424 ISBN-13(EAN): 9789819955428
Издательство: Springer
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Цена: 121110.00 T
Наличие на складе: Нет в наличии.
Описание: Big Data Analytics for Smart Urban Systems aims to introduce Big data solutions for urban sustainability smart applications, particularly for smart urban systems. It focuses on intelligent big data which takes the benefits of machine learning to analyse large and rapidly changing datasets in smart urban systems. The state-of-the-art Big data analytics applications are presented and discussed to highlight the feasibility of big data and machine learning solutions to enhance smart urban systems, smart operations, urban management, and urban governance. The key benefits of this book are, (1) to introduce the principles of machine learning-enabled big data analysis in smart urban systems, (2) to present the state-of-the-art data analysis solutions in smart management and operations, and (3) to understand the principles of big data analytics for smart cities and communities. Endorsements ‘Over the many years of collaboration between academia and industry, we noticed the common language is ‘big data’; with that, we have developed novel ideas to bridge the gaps and help promote innovation, technologies, and science’. - Tian Tang, Independent Researcher, China ‘Big Data Analytics is a fascinating research area, particularly for cities and city transformations. This book is valuable to those who think vigorously and aim to act ahead’. - Li Xie, Independent Researcher, China ‘For urban critiques, knowledge trains aspiring opportunities toward outstanding manifestations. Smartness has evolved or/ advanced rambunctious & embracing realities along (with) novel directions and nurturing integrated city knowledge’. - Aaron Golden, SELECT Consultants, UK


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