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Healthcare Data Analytics (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)

Healthcare Data Analytics (Chapman & Hall/CRC Data Mining and Knowledge Discovery Series)

At the intersection of computer science and healthcare, data analytics has emerged as a promising tool for solving problems across many healthcare-related disciplines. Supplying a comprehensive overview of recent healthcare analytics research, Healthcare Data Analytics provides a clear understanding of the analytical techniques currently available to solve healthcare problems.

The book details novel techniques for acquiring, handling, retrieving, and making best use of healthcare data. It

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Posted by mod198 May - 13 - 2015 ADD COMMENTS

Big Data Technology Series: data mining technology and engineering practice(Chinese Edition)

Big Data Technology Series: data mining technology and engineering practice(Chinese Edition)

Language:Chinese.Pub Date: 2014-10-01 Pages: 400 Publisher: Machinery Industry Press Data mining is one of the most active areas of current. Big Data Technology Series: data mining technology and engineering practice. according to his own 20 years of experience in data mining. data mining summarizes the theoretical knowledge and practical experience to provide a lot of information on line. This book introduces the concept of data mining and misunderstanding. then introduce data exploration metho

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Posted by mod198 April - 1 - 2015 ADD COMMENTS

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Mining the Social Web: Data Mining Facebook, Twitter, LinkedIn, Google+, GitHub, and More

Mining the Social Web: Data Mining Facebook, Twitter, LinkedIn, Google+, GitHub, and More

  • Used Book in Good Condition

How can you tap into the wealth of social web data to discover who’s making connections with whom, what they’re talking about, and where they’re located? With this expanded and thoroughly revised edition, you’ll learn how to acquire, analyze, and summarize data from all corners of the social web, including Facebook, Twitter, LinkedIn, Google+, GitHub, email, websites, and blogs.Employ the Natural Language Toolkit, NetworkX, and other scientific computing tools to mine popular social web

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Posted by mod198 February - 16 - 2015 ADD COMMENTS

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Farmington Hills, Mich (PRWEB) November 17, 2014

Recognizing the benefit of data analysis for the digital humanities field, Gale, part of Cengage Learning, will make available content from its Gale Digital Collections to academic researchers for data mining and textual analysis purposes. Data mining and textual analysis – the process by which text or datasets are crawled by software that recognizes entities, relationships and action – helps researchers draw new conclusions among disparate data and is emerging as an important area of scholarly research.

“Gale is taking an important, industry-leading step by making content available for researchers in this way,” said Frank Menchaca, senior vice president for global product management at Gale. “Data mining coupled with our new curriculum alignment service, in which Gale maps an institution’s library resources to specific areas of faculty research and course focus, is helping our academic customers realize even more value for their investment with Gale.”

Gale will deliver content upon customer request and in a cost-effective manner for the use of data mining and textual analysis. Content from most Gale Digital Collections, including essential research databases like Eighteenth Century Collections Online and Nineteenth Century Collections Online, as well as content from Gale’s extensive newspaper archives and other collections will be made available. In addition to content, Gale is offering new textual analysis tools within the digital archives to assist researchers who may not have programming experience or digital humanities programs at their institution. “Term cluster” and “term frequency” tools will sort through the text and index terms from the content, generating visual displays of information to help researchers easily identify relationships between words and phrases.

For more information on the program, please register for Gale’s webcast “Data Mining and Text Analytics: Gale at the Forefront of Providing Content Set,” scheduled for Wednesday, Nov. 19th at 3pm EST.

For questions or to speak with a Gale spokesperson, please contact Kristina Massari at kristina.massari@cengage.com. Interested customer may also contact their Gale representative for more information.

About Cengage Learning and Gale

Cengage Learning is a leading educational content, technology and services company, empowering educators and driving learner engagement through personalized services and course-driven digital solutions that bridge from the library to the classroom. Gale, part of Cengage Learning, serves the world’s information and education needs through its vast and dynamic content pools, which are used by students and consumers in their libraries, schools and on the Internet. It is best known for the accuracy, breadth and convenience of its data, addressing all types of information needs – from homework help to health questions to business profiles – in a variety of formats. For more information, visit http://www.cengage.com or http://www.gale.cengage.com.







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Posted by gildenshelton565 September - 6 - 2014 ADD COMMENTS

Data Science for Business: What you need to know about data mining and data-analytic thinking

Data Science for Business: What you need to know about data mining and data-analytic thinking

Written by renowned data science experts Foster Provost and Tom Fawcett, Data Science for Business introduces the fundamental principles of data science, and walks you through the “data-analytic thinking” necessary for extracting useful knowledge and business value from the data you collect. This guide also helps you understand the many data-mining techniques in use today.Based on an MBA course Provost has taught at New York University over the past ten years, Data Science for Business provides

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Data Analytics

Data Analytics

This book is a comprehensive introduction to the methods and algorithms and approaches of modern data analytics. It covers data preprocessing, visualization, correlation, regression, forecasting, classification, and clustering. It provides a sound mathematical basis, discusses advantages and drawbacks of different approaches, and enables the reader to design and implement data analytics solutions for real-world applications. The text is designed for undergraduate and graduate courses on data ana

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