Ciencia de Datos. Minería De Datos. Big Data. Técnicas Analíticas De Aprendizaje Estadístico. Un Enfoque Práctico

Translated title of the contribution: Data Science. Data mining. Big Data. Analytical Techniques of Statistical Learning. A Practical Approach

Jesús García Herrero, Antonio Berlanga De Jesús, José Manuel Molina Lopez, Miguel Ángel Patricio Guisado, Alvaro Luis Bustamante, Washington Raul Padilla Arias

Research output: Book/ReportBook

Abstract

Data science. Analytical Techniques and Statistical Learning. A practical approach brings to its readers a fresh overview of the existing techniques for data mining, which is presented through fundamental concepts and algorithms to analyze results. Through practical resources, such as case study examples and the authors' guidance that can be found as a tutorial, different knowledge extraction techniques on selected complex domains are explained, making it easy for the reader to transfer their knowledge to different fields of application. To approach such teachings, the experts use nine chapters to go through the different areas of data, with the objective of sequentially increasing the complexity of the knowledge. The reader will begin by learning what data is, what data mining is, as well as the main projects and applications of data science. Once these fundamental elements are established, a tour through statistical data analysis, prediction and classification with numerical techniques, the different data mining techniques, the internet of things and data analysis, among others, is made. With multiple knowledge presented in detail, those interested in these topics will have no doubt to solve the problems they face in these cases.
Translated title of the contributionData Science. Data mining. Big Data. Analytical Techniques of Statistical Learning. A Practical Approach
Original languageSpanish (Ecuador)
PublisherALTARIA, S.L.
Number of pages448
ISBN (Print)978-607-538-252-4
StatePublished - 28 May 2018

CACES Knowledge Areas

  • 116A Computer Science

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