Modelos Predictivos para Identificar Probabilidades de Recomendació.

Format:

Book

Author/Creator:

Raymondi, William Rafael.

Contributor:

Peña, Sergio Israel.

Series:

Tecnología Series

Tecnología Series ; v.125

Language:

English

Subjects (All):

Computadoras--Programación.

Programación de ordenadores.

Programación funcional (informática).

Local Subjects:

Computadoras--Programación.

Programación de ordenadores.

Programación funcional (informática).

Genre:

Libros electrónicos.

Physical Description:

1 online resource (109 pages)

Edition:

1st ed.

Place of Publication:

Texas : Editorial Tecnocientifica Americana (ETECAM), 2023.

Summary:

This book, authored by William Rafael Raymondi Lomas and Sergio Israel Peña Guano, focuses on the development and application of predictive models to enhance customer recommendation systems. It explores the theoretical and practical aspects of predictive modeling, emphasizing the use of technologies such as big data, machine learning, and data mining. The primary aim is to enable businesses, like the example company Distecom, to analyze customer satisfaction and improve customer experiences by predicting recommendation likelihoods. The book discusses methodologies like CRISP-DM and Kimball, and tools like Python, to develop these models. It is intended for researchers, data analysts, and business professionals interested in leveraging predictive analytics to drive business growth and customer loyalty. Generated by AI.

Notes:

Incluye índice.

Incluye bibliografía.

Description based on publisher supplied metadata and other sources.

Part of the metadata in this record was created by AI, based on the text of the resource.

OCLC:

1399431569