Match Analysis: How to Use Data in Professional Sport, Memmert Daniel
Автор: Edmond Jennifer, Mandal Anthony, Horsley Nicola Название: The Trouble with Big Data: How Datafication Displaces Cultural Practices ISBN: 1350239623 ISBN-13(EAN): 9781350239623 Издательство: Bloomsbury Academic Рейтинг: Цена: 27588.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This open access book explores the challenges society faces with big data, through the lens of culture rather than social, political or economic trends, as demonstrated in the words we use, the values that underpin our interactions, and the biases and assumptions that drive us. Focusing on areas such as data and language, data and sensemaking, data and power, data and invisibility, and big data aggregation, it demonstrates that humanities research, focussing on cultural rather than social, political or economic frames of reference for viewing technology, resists mass datafication for a reason, and that those very reasons can be instructive for the critical observation of big data research and innovation.
The eBook editions of this book are available open access under a CC BY-NC-ND 4.0 licence on bloomsburycollections.com. Open access was funded by Trinity College Dublin, DARIAH-EU and the European Commission.
Автор: Guller, Mohammed Название: Big data analytics with spark ISBN: 1484209656 ISBN-13(EAN): 9781484209653 Издательство: Springer Рейтинг: Цена: 5309.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
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.
Название: Applied matrix and tensor variate data analysis ISBN: 443155386X ISBN-13(EAN): 9784431553861 Издательство: Springer Рейтинг: Цена: 6986.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book provides comprehensive reviews of recent progress in matrix variate and tensor variate data analysis from applied points of view.
Автор: Redman Thomas C. Название: Getting in Front on Data: Who Does What ISBN: 1634621263 ISBN-13(EAN): 9781634621267 Издательство: Gazelle Book Services Рейтинг: Цена: 8792.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
This book lays out the roles everyone, up and down the organization chart, can and must play to ensure that data is up to the demands of its use, in day-in, day-out work, decision-making, planning, and analytics.
By now, everyone knows that bad data extorts an enormous toll, adding huge (though often hidden) costs, and making it more difficult to make good decisions and leverage advanced analyses. While the problems are pervasive and insidious, they are also solvable As Tom Redman, "the Data Doc," explains in Getting in Front on Data, the secret lies in getting the right people in the right roles to "get in front" of the management and social issues that lead to bad data in the first place.
Everyone should see himself or herself in this book. We are all both data customers and data creators--after all, we use data created by others and create data used by others. And all of us must step up to these roles. As data customers, we must clarify our most important needs and communicate them to data creators. As data creators, we must strive to meet those needs by finding and eliminating the root causes of error.
Getting in Front on Data proposes new roles for data professionals as:
embedded data managers, in helping data customers and creators complete their work,
DQ team leads, in connecting customers and creators, pulling the entire program together, and training people on their new roles,
data maestros, in providing deep expertise on the really tough problems,
chief data architects, in establishing common data definitions, and
technologists, in increasing scale and decreasing unit cost.
Getting in Front on Data introduces a new role, the data provocateur, the motive force in attacking data quality properly This book urges everyone to unleash their inner provocateur.
Finally, it crystallizes what senior leaders must do if their entire organizations are to enjoy the benefits of high-quality data
Описание: The text explains the model-based method of intelligence analysis that represents the analyst`s mental models of a subject as well as the analyst`s reasoning process. It includes dynamic simulations and interactive analytic games, case studies that illustrate a wide range of intelligence problems, and a recommended curriculum for technical analysts.
Автор: Marc Potters, Jean-Philippe Bouchaud Название: A First Course in Random Matrix Theory ISBN: 1108488080 ISBN-13(EAN): 9781108488082 Издательство: Cambridge Academ Рейтинг: Цена: 9186.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Classical statistical tools that handled real-life data have become inadequate upon the emergence of Big Data. Random matrix theory and free calculus introduced here present valuable solutions to the complex challenges posed by large datasets. Real world applications make it an essential tool for physicists, engineers, data analysts and economists.
Автор: Memmert, Daniel Название: Match Analysis ISBN: 0367750945 ISBN-13(EAN): 9780367750947 Издательство: Taylor&Francis Рейтинг: Цена: 22202.00 р. Наличие на складе: Поставка под заказ.
Автор: Waltz, Edward Название: Quantitative intelligence analysis ISBN: 0810895463 ISBN-13(EAN): 9780810895461 Издательство: Rowman & Littlefield Publishers Рейтинг: Цена: 6336.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: The text explains the model-based method of intelligence analysis that represents the analyst`s mental models of a subject as well as the analyst`s reasoning process. It includes dynamic simulations and interactive analytic games, case studies that illustrate a wide range of intelligence problems, and a recommended curriculum for technical analysts.
Автор: MacLean Dan Название: R Bioinformatics Cookbook ISBN: 1789950694 ISBN-13(EAN): 9781789950694 Издательство: Неизвестно Рейтинг: Цена: 11033.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book discusses the complexities inherent in preserving and interpreting the extraordinary range of culturally significant objects entrusted to museums. From how museums acquire their holdings, to how they are conserved, to how accessible they are, the book presents an encompassing look at every aspect of the duties museum by definition assume
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This guidebook went through all of the steps that you need to know in order to get started with data science and some of the basic parts of the Python code. We can then put all of this together in order to create the right analytical algorithm that, once it is trained properly and tested with the right kinds of data, will work to make predictions, provide information, and even show us insights that were never possible before. And all that you need to do to get this information is to use the steps that we outline and discuss in this guidebook.
There is a lot of buzz in the business world, no matter what industry it is, about machine learning, the Python language, and of course, data science, and being able to put these terms together and learn how they work can make a big difference in how well your business will do now and in the future. There are already a ton of companies out there who have been able to gain a competitive edge with data science and the various models and algorithms of Python that go with it, and you can as well.
This book covers:
What is Data Science?
The Python Coding Language
Some of the Basic Coding in Python
The Best Python Libraries to Use with Data Science
The Basics of Jupyter and Why We Should Use It
Working with Anaconda in Python
The Basics of the Pandas Library
What is WinPython and How Can We Use It?
Common Tasks to Do in Info Science
Different Data Types to Work With
The Future of Data Science and Where It Will Go from Here
There are so many great ways that you can use the data you have been collecting for some time now and being able to complete the process of data visualization will ensure that you get it all done. When you are ready to get started with Python data science, make sure to check out this guidebook to learn how.
There is so much that can come into play when we work with data science, and it is one of the best ways for a business to differentiate from the competition and actually see some results in the process. And the Python language is a great option to learn to help us analyze and create a model that works with the info that we have. When we are ready to learn more about data science, and how to use the Python coding language to go with it, make sure to check out this guidebook to help you get started.
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