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Business analytics with R and Python

Olson, David L.

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Business analytics with R and Python

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Business analytics with R and Python/ by David L. Olson ... [et al.].
其他作者:	Olson, David L.
出版者:	Singapore :Springer Nature Singapore : : 2024.,
面頁冊數:	x, 196 p. :ill. (chiefly col.), digital ;24 cm.
內容註:	Data Mining in Business -- Data Mining Processes -- Data Mining Software -- Association Rules -- Cluster Analysis -- Regression Algorithms in Data Mining -- Classification Tools -- Variable Selection -- Dataset Balancing.
Contained By:	Springer Nature eBook
標題:	Business - Data processing. -
電子資源:	https://doi.org/10.1007/978-981-97-4772-6
ISBN:	9789819747726

Business analytics with R and Python
Business analytics with R and Python[electronic resource] /by David L. Olson ... [et al.]. - Singapore :Springer Nature Singapore :2024. - x, 196 p. :ill. (chiefly col.), digital ;24 cm. - AI for risks,2731-6335. - AI for risks..

Data Mining in Business -- Data Mining Processes -- Data Mining Software -- Association Rules -- Cluster Analysis -- Regression Algorithms in Data Mining -- Classification Tools -- Variable Selection -- Dataset Balancing.

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.

ISBN: 9789819747726

Standard No.: 10.1007/978-981-97-4772-6doiSubjects--Topical Terms:

527441
Business
--Data processing.

LC Class. No.: HF5548.2

Dewey Class. No.: 658.05

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