Preview "Machine Learning for Business Analytics (2nd ed.)" in a new window.

Machine Learning for Business Analytics (2nd ed.)

Authors

Book Description

Machine Learning for Business Analytics: Concepts, Techniques, and Applications in Python is a comprehensive introduction to and an overview of the methods that underlie modern AI. This best-selling textbook covers both statistical and machine learning (AI) algorithms for prediction, classification, visualization, dimension reduction, rule mining, recommendations, clustering, text mining, experimentation, network analytics and generative AI. Along with hands-on exercises and real-life case studies, it also discusses managerial and ethical issues for responsible use of machine learning techniques.

This is the second Python edition of Machine Learning for Business Analytics. This edition also includes: A new chapter on generative AI (large language models or LLMs, and image generation)An expanded chapter on deep learningA new chapter on experimental feedback techniques including A/B testing, uplift modeling, and reinforcement learningA new chapter on responsible data scienceUpdates and new material based on feedback from instructors teaching MBA, Masters in Business Analytics and related programs, undergraduate, diploma and executive courses, and from their studentsA full chapter of cases demonstrating applications for the machine learning techniquesEnd-of-chapter exercises with dataA companion website with more than two dozen data sets, and instructor materials including exercise solutions, slides, and case solutions

This textbook is an ideal resource for upper-level undergraduate and graduate level courses in AI, data science, predictive analytics, and business analytics. It is also an excellent reference for analysts, researchers, and data science practitioners working with quantitative data in management, finance, marketing, operations management, information systems, computer science, and information technology.

In The Press

About the Author

Read on Your Favourite Devices

to find out more

Ebook Permissions

to find out more

About this Ebook

File formats
This ebook is available in:
The publisher has not yet supplied format information.
Pre-order formats shown are based on publisher intent and may change before release.
File sizes shown are an approximation. The actual download size will vary based on the application you use to read the book.
Publisher
Published
; Copyright:
ISBNs
Title
Series
Author
;
Edition
Imprint
Language
Number of Pages
Page count shown is an approximation provided by the publisher. The actual page count will vary based on various factors such as your device's screen size and font-size.