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End to end Data Analytics for Product Development, Luigi Salmaso, Mattia De Dominicis, Rosa Arboretti


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Цена: 11397.00р.
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При оформлении заказа до: 2025-08-04
Ориентировочная дата поставки: Август-начало Сентября
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Автор: Luigi Salmaso, Mattia De Dominicis, Rosa Arboretti
Название:  End to end Data Analytics for Product Development
ISBN: 9781119483694
Издательство: Wiley
Классификация:


ISBN-10: 1119483697
Обложка/Формат: Hardback
Страницы: 312
Вес: 0.58 кг.
Дата издания: 20.02.2020
Серия: No longer used
Язык: English
Размер: 230 x 162 x 22
Читательская аудитория: Professional & vocational
Ключевые слова: Mathematics,Probability & statistics
Основная тема: Mathematics,Probability & statistics
Подзаголовок: A practical guide for fast consumer goods companies, chemical industry and processing tools manufacturers
Ссылка на Издательство: Link
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Поставляется из: Англии
Описание:

An interactive guide to the statistical tools used to solve problems during product and process innovation

End to End Data Analytics for Product Development is an accessible guide designed for practitioners in the industrial field. It offers an introduction to data analytics and the design of experiments (DoE) whilst covering the basic statistical concepts useful to an understanding of DoE. The text supports product innovation and development across a range of consumer goods and pharmaceutical organizations in order to improve the quality and speed of implementation through data analytics, statistical design and data prediction.

The book reviews information on feasibility screening, formulation and packaging development, sensory tests, and more. The authors - noted experts in the field - explore relevant techniques for data analytics and present the guidelines for data interpretation. In addition, the book contains information on process development and product validation that can be optimized through data understanding, analysis and validation. The authors present an accessible, hands-on approach that uses MINITAB and JMP software. The book:

- Presents a guide to innovation feasibility and formulation and process development

- Contains the statistical tools used to solve challenges faced during product innovation and feasibility

- Offers information on stability studies which are common especially in chemical or pharmaceutical fields

- Includes a companion website which contains videos summarizing main concepts

Written for undergraduate students and practitioners in industry, End to End Data Analytics for Product Development offers resources for the planning, conducting, analyzing and interpreting of controlled tests in order to develop effective products and processes.




Healthcare Analytics

Автор: Rafalski, Edward M. | Mu
Название: Healthcare Analytics
ISBN: 1138196363 ISBN-13(EAN): 9781138196360
Издательство: Taylor&Francis
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Цена: 5511.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание: This is a comprehensive, practical guide which looks at the advantages and limitations of new data analysis techniques being introduced across public health and administration services.

SAS for R Users: Data Science and Business Analyti cs

Автор: Ohri
Название: SAS for R Users: Data Science and Business Analyti cs
ISBN: 1119256410 ISBN-13(EAN): 9781119256410
Издательство: Wiley
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Цена: 14565.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание:

Professor Pippy P. Poopypants may be the greatest scientific genius the world has ever known. Unfortunately, he has such a silly name that nobody takes him seriously! He`s been laughed out of every major university in the world.

In fact, the only place that`ll hire him is Jerome Horwitz Elementary School. Hopefully, nobody at the school will laugh at his name (or make a comic book about him)....

...Because if just one more person makes fun of Poopypants, it might just drive him OFF THE DEEP END!

Needless to say, George and Harold poo-poo Poopypants`s pride -- practically pulverizing it to pieces -- and, hence, Poopypants is preparing to pounce!

Step up to witness a brief encounter of the cottony kind. This looks exactly like a job for The Amazing CAPTAIN UNDERPANTS!

Jorge y Berto no son malos chicos. Lo que pasa es que les gusta animar las cosas de vez en cuando. Asi, sin proponerselo, estan a punto de hacer que el profesor Pipicaca, un cientifico enloquecido y sin escrupulos que se encuentra a bordo de un robot gigantesco, se apodere del planeta entero. Quien desbaratara los perversos planes de Pipicaca? Un nuevo trabajo para el Capitan Calzoncillos!

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.
Data Mining for Business Analytics: Concepts, Techniques, and Applications with XLMiner

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
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Цена: 17741.00 р.
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.

Harness Oil and Gas Big Data with Analytics

Автор: Holdaway Keith
Название: Harness Oil and Gas Big Data with Analytics
ISBN: 1118779312 ISBN-13(EAN): 9781118779316
Издательство: Wiley
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Цена: 9108.00 р.
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Описание: Use big data analytics to efficiently drive oil and gas exploration and production Harness Oil and Gas Big Data with Analytics provides a complete view of big data and analytics techniques as they are applied to the oil and gas industry.

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: 39130.00 р.
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.


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