Name: Handbook of Research on big Data Clustering and Machine Learning (Advances in Data Mining and Database Management) (en Inglés)
Price: 488630.00 CLP
Availability: InStock
Author: Fausto Pedro Garcia Marquez
ISBN: 9781799801061

portada Handbook of Research on big Data Clustering and Machine Learning (Advances in Data Mining and Database Management) (en Inglés)

Formato

Libro Físico

Editorial

Engineering Science Reference

Autor

Fausto Pedro Garcia Marquez

Año

2019

Idioma

Inglés

N° páginas

478

Encuadernación

Tapa Dura

ISBN13

9781799801061

N° edición

Categorías

Ciencia y análisis de datos
Análisis y captura de datos

Handbook of Research on big Data Clustering and Machine Learning (Advances in Data Mining and Database Management) (en Inglés)

Fausto Pedro Garcia Marquez (Autor) · Engineering Science Reference · Tapa Dura

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Reseña del libro "Handbook of Research on big Data Clustering and Machine Learning (Advances in Data Mining and Database Management) (en Inglés)"

As organizations continue to develop, there is an increasing need for technological methods that can keep up with the rising amount of data and information that is being generated. Machine learning is a tool that has become powerful due to its ability to analyze large amounts of data quickly. Machine learning is one of many technological advancements that is being implemented into a multitude of specialized fields. An extensive study on the execution of these advancements within professional industries is necessary.Advanced Multi-Industry Applications of Big Data Clustering and Machine Learning is an essential reference source that synthesizes the analytic principles of clustering and machine learning to big data and provides an interface between the main disciplines of engineering/technology and the organizational, administrative, and planning abilities of management. Featuring research on topics such as project management, contextual data modeling, and business information systems, this book is ideally designed for engineers, economists, finance officers, marketers, decision makers, business professionals, industry practitioners, academicians, students, and researchers seeking coverage on the implementation of big data and machine learning within specific professional fields.