Автор: Galit Shmueli, Peter C. Bruce, Nitin R. Patel Название: Data Mining for Business Analytics: Concepts, Techniques, and Applications with XLMiner ISBN: 1118729277 ISBN-13(EAN): 9781118729274 Издательство: Wiley Рейтинг: Цена: 118270.00 T Наличие на складе: Поставка под заказ. Описание: Data Mining for Business Analytics: Concepts, Techniques, and Applications in XLMiner(R), Third Edition presents an applied approach to data mining and predictive analytics with clear exposition, hands-on exercises, and real-life case studies.
Автор: Wolfe, Douglas Schneider, Grant Название: Primer for data analytics and graduate study in statistics ISBN: 303047478X ISBN-13(EAN): 9783030474782 Издательство: Springer Рейтинг: Цена: 55890.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: Advanced undergraduate students and introductory graduate students from a variety of quantitative backgrounds will benefit from the transitional bridge that this volume offers, from a more generalized study of undergraduate mathematics and statistics to the career-focused, applied education at the graduate level.
Chapter 1. Introduction.- Chapter 2. Sets, Venn diagrams, Probability and Bayes' Rule.- Chapter 3. Concept of a random variable.- Chapter 4. Multiple random variables and their Characteristics.- Chapter 5. Applications to Data Analytics and Modeling.
Автор: Y. Z. Ma Название: Quantitative Geosciences: Data Analytics, Geostatistics, Reservoir Characterization and Modeling ISBN: 3030178625 ISBN-13(EAN): 9783030178628 Издательство: Springer Рейтинг: Цена: 111790.00 T Наличие на складе: Поставка под заказ. Описание: As the petroleum industry is heading towards operating oil fields digitally, a multidisciplinary skillset is a must for geoscientists who need to use data analytics to resolve inconsistencies in various sources of data, model reservoir properties, evaluate uncertainties, and quantify risk for decision making.
Автор: Huang, Shuai Deng, Houtao Название: Data analytics ISBN: 0367609509 ISBN-13(EAN): 9780367609504 Издательство: Taylor&Francis Рейтинг: Цена: 76550.00 T Наличие на складе: Невозможна поставка. Описание: Highlights a combination of two aspects: technical concreteness and holistic thinking. Authors discuss what principles are used to invent these techniques, what assumptions are made, how mathematics is used to articulate these assumptions, and how these formulations generalize a range of real-world applications into generic and abstract forms.
Автор: Iman Rahimi, Amir H. Gandomi, Simon James Fong Название: Big data analytics in supply chain management ISBN: 0367407175 ISBN-13(EAN): 9780367407179 Издательство: Taylor&Francis Рейтинг: Цена: 168430.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book discusses the results of a recent large-scale achievement on Big Data Analytics (BDA) topics among Supply Chain Management (SCM) professionals The book intends to show a diversity of supply chain management issues that may benefit from BDA, both in theory and practice.
Автор: Gressel, Simone Pauleen, David Taskin, Nazim Название: Management decision-making, big data and analytics ISBN: 1526492008 ISBN-13(EAN): 9781526492005 Издательство: Sage Publications Рейтинг: Цена: 48570.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: An exciting new textbook examining big data and business analytics to look at how they can help managers become more effective decision-makers.
Автор: Antoniou, Constantinos Название: Mobility Patterns, Big Data and Transport Analytics ISBN: 0128129700 ISBN-13(EAN): 9780128129708 Издательство: Elsevier Science Рейтинг: Цена: 110030.00 T Наличие на складе: Поставка под заказ. Описание:
Transportation modelers and analysts face new opportunities and challenges in the study of mobility patterns and transportation systems, thanks to the advent of paradigm-shifting big data. Mobility Patterns, Big Data and Transport Analytics: Tools and Applications provides a guide to this new analytical framework related to big data, focusing on capturing, predicting, visualizing and controlling mobility patterns - a key aspect of transportation modeling.
Transportation systems analysis relies upon assumptions related to social, collective, personal, or disaggregate organization of desires expressed by the mobility of people or goods. Recent advances in information technology - such as available data from open sources, participation in media platforms, and sensor technologies - have created an environment of great change, and the potential for transportation structural reorganization. Mobility Patterns, Big Data and Transport Analytics: Tools and Applications features prominent international expert overview on these new analytical frameworks, applications, and concepts in mobility analysis and transportation systems.
The book covers in detail, mobility 'structural' analysis (and its dynamics), the extensive behavioral characteristics of transport, observability requirements and limitations for realistic transportation applications, and transportation systems analysis related to complex processes and phenomena. The book bridges the gap between big data, data science, and Transportation Systems Analysis with a study of big data's impact on mobility, and an introduction to the tools necessary to apply new techniques.
Guides readers through the paradigm-shifting opportunities and challenges of handling Big Data in transportation modeling and analytics
Covers current analytical innovations focused on capturing, predicting, visualizing, and controlling mobility patterns, while discussing future trends
Delivers an introduction to transportation-related information advances, providing a benchmark reference by world-leading experts in the field
Captures and manages mobility patterns, covering multiple purposes and alternative transport modes, in a multi-disciplinary approach
Companion website features videos showing the analyses performed, as well as test codes and data-sets, allowing readers to recreate the presented analyses and apply the highlighted techniques to their own data
Автор: Madjid Tavana; Srikanta Patnaik Название: Recent Developments in Data Science and Business Analytics ISBN: 3030102599 ISBN-13(EAN): 9783030102593 Издательство: Springer Рейтинг: Цена: 139750.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This edited volume is brought out from the contributions of the research papers presented in the International Conference on Data Science and Business Analytics (ICDSBA- 2017), which was held during September 23-25 2017 in ChangSha, China. As we all know, the field of data science and business analytics is emerging at the intersection of the fields of mathematics, statistics, operations research, information systems, computer science and engineering. Data science and business analytics is an interdisciplinary field about processes and systems to extract knowledge or insights from data. Data science and business analytics employ techniques and theories drawn from many fields including signal processing, probability models, machine learning, statistical learning, data mining, database, data engineering, pattern recognition, visualization, descriptive analytics, predictive analytics, prescriptive analytics, uncertainty modeling, big data, data warehousing, data compression, computer programming, business intelligence, computational intelligence, and high performance computing among others. The volume contains 55 contributions from diverse areas of Data Science and Business Analytics, which has been categorized into five sections, namely: i) Marketing and Supply Chain Analytics; ii) Logistics and Operations Analytics; iii) Financial Analytics. iv) Predictive Modeling and Data Analytics; v) Communications and Information Systems Analytics. The readers shall not only receive the theoretical knowledge about this upcoming area but also cutting edge applications of this domains.
Автор: Gressel, Simone Pauleen, David Taskin, Nazim Название: Management decision-making, big data and analytics ISBN: 1526492016 ISBN-13(EAN): 9781526492012 Издательство: Sage Publications Рейтинг: Цена: 147840.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: An exciting new textbook examining big data and business analytics to look at how they can help managers become more effective decision-makers.
Автор: Wong Ka-Chun Название: Big Data Analytics in Genomics ISBN: 3319823124 ISBN-13(EAN): 9783319823126 Издательство: Springer Рейтинг: Цена: 158380.00 T 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: Mathar Rudolf, Alirezaei Gholamreza, Balda Emilio Название: Fundamentals of Data Analytics: With a View to Machine Learning ISBN: 303056830X ISBN-13(EAN): 9783030568306 Издательство: Springer Рейтинг: Цена: 60550.00 T Наличие на складе: Есть у поставщика Поставка под заказ. Описание: This book introduces the basic methodologies for successful data analytics. The methodological overlap between data science and machine learning is emphasized by demonstrating how data science is used for classification as well as supervised and unsupervised learning.
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