UID:
almafu_9961437213802883
Format:
1 online resource (109 pages)
Edition:
1st ed.
Series Statement:
Tecnología Series ; v.125
Content:
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.
Note:
Incluye índice.
Additional Edition:
ISBN 9780311000470
Additional Edition:
ISBN 0311000479
Language:
English
Keywords:
Libros electrónicos.
;
Libros electrónicos.
