0 Mėgstami
0Krepšelis
107,23 
107,23 
2025-07-31 107.2300 InStock
Nemokamas pristatymas į paštomatus per 18-22 darbo dienų užsakymams nuo 19,00 

Knygos aprašymas

This book provides an overview of data mining methods in the field of business. Business management faces challenges in serving customers in better ways, in identifying risks, and analyzing the impact of decisions. Of the three types of analytic tools, descriptive analytics focuses on what has happened and predictive analytics extends statistical and/or artificial intelligence to provide forecasting capability. Chapter 1 provides an overview of business management problems. Chapter 2 describes how analytics and knowledge management have been used to better cope with these problems. Chapter 3 describes initial data visualization tools. Chapter 4 describes association rules and software support. Chapter 5 describes cluster analysis with software demonstration. Chapter 6 discusses time series analysis with software demonstration. Chapter 7 describes predictive classification data mining tools. Applications of the context of management are presented in Chapter 8. Chapter 9 covers prescriptive modeling in business and applications of artificial intelligence.

Informacija

Autorius: David L. Olson, Desheng Dash Wu, Cuicui Luo, Majid Nabavi,
Leidėjas: Springer Nature Singapore
Išleidimo metai: 2024
Knygos puslapių skaičius: 208
ISBN-10: 9819747716
ISBN-13: 9789819747719
Formatas: Knyga kietu viršeliu
Kalba: Anglų
Žanras: Business mathematics and systems

Pirkėjų atsiliepimai

Parašykite atsiliepimą apie „Business Analytics with R and Python“

Būtina įvertinti prekę

Goodreads reviews for „Business Analytics with R and Python“