Name: Mining Over Air: Wireless Communication Networks Analytics (en Inglés)
Price: 138110.00 CLP
Availability: InStock
Author: Ouyang, Ye ; Hu, Mantian ; Huet, Alexis
ISBN: 9783030064037

portada Mining Over Air: Wireless Communication Networks Analytics (en Inglés)

Formato

Libro Físico

Autor

Editorial

Idioma

Inglés

N° páginas

196

Encuadernación

Tapa Blanda

Dimensiones

23.4 x 15.6 x 1.1 cm

Peso

0.30 kg.

ISBN13

9783030064037

Categorías

Hardware de redes
Algoritmos y estructuras de datos
Data mining: minería de datos

Mining Over Air: Wireless Communication Networks Analytics (en Inglés)

Ye Ouyang (Autor) · Mantian Hu (Autor) · Alexis Huet (Autor) · Springer · Tapa Blanda

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$ 138.110

$ 251.110

Ahorras: $ 113.000

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Envío normal

Origen: Estados Unidos (Costos de importación incluídos en el precio)

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Reseña del libro "Mining Over Air: Wireless Communication Networks Analytics (en Inglés)"

This book introduces the concepts, applications and development of data science in the telecommunications industry by focusing on advanced machine learning and data mining methodologies in the wireless networks domain. Mining Over Air describes the problems and their solutions for wireless network performance and quality, device quality readiness and returns analytics, wireless resource usage profiling, network traffic anomaly detection, intelligence-based self-organizing networks, telecom marketing, social influence, and other important applications in the telecom industry. Written by authors who study big data analytics in wireless networks and telecommunication markets from both industrial and academic perspectives, the book targets the pain points in telecommunication networks and markets through big data. Designed for both practitioners and researchers, the book explores the intersection between the development of new engineering technology and uses data from the industry to understand consumer behavior. It combines engineering savvy with insights about human behavior. Engineers will understand how the data generated from the technology can be used to understand the consumer behavior and social scientists will get a better understanding of the data generation process.