Business analytics with Python : essential skills for business students / Bowei Chen and Gerhard Kling.

By:

Chen, Bowei [author.]

Contributor(s):

Kling, Gerhard (Professor of finance) [author.]

Material type: Text

TextPublisher: London ; New York, NY : Kogan Page Limted, 2025Description: 440 pages ; 24 cmISBN:

9781398617179

Subject(s):

Additional physical formats: Online version:: Business analytics with PythonLOC classification:

HD30.2 .C728 2025

Contents:

Mathematical foundations of business analytics — Getting started with Python — Data wrangling — Data visualization — Linear regression — Logistic regression — Neural networks — K-nearest neighbours — Naïve Bayes — Tree-based methods — Support vector machines — Principal component analysis — Cluster analysis — Modelling supply chains – use cases — User interfaces and web applications — Answers to exercises.

Summary: For business school students learning about business analytics, and business professionals seeking practical guidance concerning the skills and techniques that business analytics require, this comprehensive volume is quite simply a must-read. It goes beyond mere theory to illuminate the practical uses of business analytics applicable to real-world situations. This volume is thoughtful, intelligent, well-written and curated, yet readily accessible, providing clear explanations and pertinent insights, while ensuring that the mathematical content remains at a level that readers can understand. I have found it to be invaluable and illuminating, making business analytics intelligible to the interested reader who may not yet be familiar with all that business analytics has to offer.Professor Mairi Maclean, Professor of International Business, School of Management, University of Bath, UK Provided by publisher.Summary: Data-driven decision-making is a fundamental component of business success. Use this textbook to help you learn and understand the core knowledge and techniques needed for analysing business data with Python programming. Business Analytics with Python is ideal for students taking upper level undergraduate and postgraduate modules on analytics as part of their business, management or finance degrees. It assumes no prior knowledge or experience in computer science, instead presenting the technical aspects of the subject in an accessible, introductory way for students. This book takes a holistic approach to business analytics, covering not only Python as well as mathematical and statistical concepts, essential machine learning methods and their applications.

List(s) this item appears in: PYTHON

Holdings ( 1 )
Title notes ( 4 )

Holdings
Item type	Current library	Call number	Copy number	Status	Date due	Barcode
Book	TBS Barcelona	HD30.2 CHE (Browse shelf(Opens below))	1	Available		B05741

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Includes bibliographical references and index.

For business school students learning about business analytics, and business professionals seeking practical guidance concerning the skills and techniques that business analytics require, this comprehensive volume is quite simply a must-read. It goes beyond mere theory to illuminate the practical uses of business analytics applicable to real-world situations. This volume is thoughtful, intelligent, well-written and curated, yet readily accessible, providing clear explanations and pertinent insights, while ensuring that the mathematical content remains at a level that readers can understand. I have found it to be invaluable and illuminating, making business analytics intelligible to the interested reader who may not yet be familiar with all that business analytics has to offer.Professor Mairi Maclean, Professor of International Business, School of Management, University of Bath, UK Provided by publisher.

Data-driven decision-making is a fundamental component of business success. Use this textbook to help you learn and understand the core knowledge and techniques needed for analysing business data with Python programming.

Business Analytics with Python is ideal for students taking upper level undergraduate and postgraduate modules on analytics as part of their business, management or finance degrees. It assumes no prior knowledge or experience in computer science, instead presenting the technical aspects of the subject in an accessible, introductory way for students. This book takes a holistic approach to business analytics, covering not only Python as well as mathematical and statistical concepts, essential machine learning methods and their applications.