Business Analytics With Python

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Business Analytics With Python

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Author : Bowei Chen
language : en
Publisher: Kogan Page Publishers
Release Date : 2025-03-03

Business Analytics With Python written by Bowei Chen and has been published by Kogan Page Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-03 with Computers categories.

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. Features include: - Chapters covering preliminaries, as well as supervised and unsupervised machine learning techniques - A running case study to help students apply their knowledge in practice. - Real-life examples demonstrating the use of business analytics for tasks such as customer churn prediction, credit card fraud detection, and sales forecasting. - Practical exercises and activities, learning objectives, and chapter summaries to support learning.

Data Mining For Business Analytics

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Author : Galit Shmueli
language : en
Publisher: John Wiley & Sons
Release Date : 2017-09-12

Data Mining For Business Analytics written by Galit Shmueli and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-12 with Mathematics categories.

Data Mining for Business Analytics: Concepts, Techniques, and Applications in R presents an applied approach to data mining concepts and methods, using R software for illustration Readers will learn how to implement a variety of popular data mining algorithms in R (a free and open-source software) to tackle business problems and opportunities. This is the fifth version of this successful text, and the first using R. It covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, recommender systems, clustering, text mining and network analysis. It also includes: Two new co-authors, Inbal Yahav and Casey Lichtendahl, who bring both expertise teaching business analytics courses using R, and data mining consulting experience in business and government Updates and new material based on feedback from instructors teaching MBA, undergraduate, diploma and executive courses, and from their students More than a dozen case studies demonstrating applications for the data mining techniques described End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented A companion website with more than two dozen data sets, and instructor materials including exercise solutions, PowerPoint slides, and case solutions www.dataminingbook.com Data Mining for Business Analytics: Concepts, Techniques, and Applications in R is an ideal textbook for graduate and upper-undergraduate level courses in data mining, predictive analytics, and business analytics. This new edition is also an excellent reference for analysts, researchers, and practitioners working with quantitative methods in the fields of business, finance, marketing, computer science, and information technology.

Python For Business Analytics

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Author : Mahadi Hasan Miraz
language : en
Publisher: Springer Nature
Release Date : 2025-08-14

Python For Business Analytics written by Mahadi Hasan Miraz and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-14 with Computers categories.

This book provides a thorough introduction to Python, specifically designed for those in business analytics. It starts with the fundamentals of Python and gradually covers more advanced topics, including data manipulation, visualization, and analytics techniques. The content is structured to help readers build a strong foundation in Python, essential for success in data science and business analytics. The book also features real-world case studies and practical examples, demonstrating how Python can be applied in business decision-making. These insights make it a valuable resource for students and professionals who want to use Python to solve real business problems. Python's importance in today’s data-driven industries cannot be overstated. Proficiency in this programming language enhances the ability to tackle complex challenges and supports strategic decision-making. For organizations, Python enables the setting of data-driven goals, improved performance, and the fostering of continuous learning. Its open-source nature and wide range of online resources make it accessible to everyone, ensuring that users are equipped with the skills needed in a rapidly evolving workplace. This book serves as a comprehensive guide for those aiming to excel in the field of business analytics through the effective use of Python.

Python For Data Science

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Author : Jason Callaway
language : en
Publisher:
Release Date : 2020-11-25

Python For Data Science written by Jason Callaway and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-25 with Computers categories.

If you are a student or a professional looking for more technical skills, or if you are simply curious about the most up-to-date data analysis techniques and their powerful applications, then this is definitely the book for you. Learning all of the required skills to master data science and machine learning could certainly be challenging, but in this book, Jason Callaway has condensed all of the knowledge you need into a clear and beginner-friendly introduction, with practical examples, detailed explanations, and tips and tricks from his experience. Through his revolutionary and systematic approach, you can learn techniques to manipulate and process datasets, the principles of Python programming, and their real-world applications, regardless of your previous experience. Here's just a tiny fraction of what you will discover: What data science is, and why it has become fundamental in hundreds of business and technological applications The basics of Python programming Essential Python libraries such as NumPy, Pandas, and Matplotlib All of the most effective computational methods for data analysis Data visualization tools and techniques How to build statistical and machine learning models (even if you are brand new to programming) The future of Artificial Intelligence How to build neural networks with Python Step-by-step exercises, practical examples, and tips and tricks Are you ready to develop a successful career in the growing industry of data science?

Business Analytics Using Python

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Author : Kumar P
language : en
Publisher: Independently Published
Release Date : 2024-11-20

Business Analytics Using Python written by Kumar P and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-20 with Computers categories.

In today's fast-paced and data-driven world, businesses are increasingly relying on data to guide their strategies, optimize operations, and stay ahead of the competition. From customer behavior to market trends, every facet of a business generates vast amounts of data-data that holds the key to better decision-making, enhanced performance, and greater profitability. However, unlocking the potential of this data requires more than just access to it; it requires the tools, techniques, and frameworks that allow us to analyze, interpret, and act on the insights it provides. This book, Business Analytics using Python: Practical Approaches to Data-Driven Decision Making, is designed to provide you with the knowledge and practical skills necessary to leverage the power of data in business contexts. Whether you are a business analyst, data scientist, or business manager, this book aims to equip you with a solid foundation in business analytics using Python, one of the most powerful and widely used open-source programming languages for statistical analysis and data science. Python has become an indispensable tool in the world of analytics. Its flexibility, vast library of packages, and user-friendly environment make it ideal for analyzing and visualizing data, building predictive models, and uncovering trends that drive business success. In this book, we will guide you through the fundamentals of Python, as well as advanced techniques in business analytics, with a focus on solving real-world business problems. In addition to the theoretical underpinnings of business analytics, the book is packed with hands-on examples, practical exercises, and case studies that demonstrate how these concepts are applied in real-world business scenarios. Whether you are trying to optimize marketing campaigns, improve sales forecasts, or understand customer behavior, the tools and techniques you will learn in this book will help you derive actionable insights from your data. Who Should Read This Book? This book is aimed at anyone interested in applying business analytics to solve real-world problems using Python. It is ideal for: Business Analysts: Who want to enhance their analytical skills and learn how to use Python for solving business problems. Data Scientists: Who are looking to expand their knowledge in business contexts and understand how to apply advanced analytics in a business environment. Managers and Decision Makers: Who want to understand how data-driven insights can inform strategic business decisions. Students and Beginners: Who are learning business analytics, data science, or related fields and want a practical guide to applying analytics using Python. This book is structured to cater to both beginners and more advanced users. Each chapter begins with a conceptual introduction to the topic, followed by practical, hands-on examples using Python. You will find step-by-step instructions, along with clear explanations of the code and the business implications of the results. Whether you are working through the chapters in order or focusing on specific topics, you will gain the skills necessary to apply business analytics in your organization. So, let's dive in and begin unlocking the true potential of your business data with Python!

Mastering Business Analytics With Python R

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Author : Manas Pandey
language : en
Publisher: Independently Published
Release Date : 2024-02-05

Mastering Business Analytics With Python R written by Manas Pandey and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-02-05 with Business & Economics categories.

"Mastering Business Analytics with Python & R: Theory and Practice" is a comprehensive guide unlocking the principles and applications of Business Analytics (BA). 5 Key Learning Outcomes or Takeaways from "Mastering Business Analytics with Python & R: Theory and Practice." 1. Demystifying Business Analytics (BA) for Informed Decision-Making: Takeaway: Gain a deep understanding of how BA empowers data-driven decisions, replacing intuition with concrete evidence. 2. Practical Applications Across Marketing, Finance, Operations, and HR: Takeaway: Discover real-world use cases of BA in diverse business functions, solving problems and optimizing performance in marketing, finance, operations, and HR. 3. Mastering Data Management and Wrangling: Takeaway: Develop essential data handling skills, including cleaning, transforming, imputing and transforming messy data into a usable format for analysis. 4. Drawing Key Insights and Recommendations: Takeaway: Learn powerful techniques for analyzing data with descriptive and inferential statistics, uncovering trends, patterns and translating them into actionable business recommendations. 5. Mastering Visualization and Predictive Modeling: Takeaway: Create impactful data visualizations using Python and R libraries, and leverage predictive modeling techniques to forecast future trends and outcomes. What you'll discover: Data Mastery: Conquer data wrangling with powerful Python libraries like pandas, NumPy and R packages like dplyr and tidyr, transforming messy data into a clean, usable format for analysis. Visual Insights: Craft compelling data visualizations using Python libraries like Matplotlib and Seaborn and R packages like ggplot2(grammar of graphics), effectively communicating insights to stakeholders. Statistical Prowess: Employ powerful statistical models in Python libraries like Scikit-learn and Statsmodels and R packages like moments, uncovering patterns, trends, and relationships within your data. Machine Learning(ML) Expertise: Understand in simple terms the mathematical aspect of ML algorithms (Decision tree, Neural Net, SVM, Clustering, etc). Build and deploy machine learning models in Python libraries like tensorflow, sklearn, Pytorch and R packages like caret, rpart, e1071, xgboost, etc. anticipating future trends and predicting business outcomes. Beyond the Basics: Application of BA in Marketing, Operations, Finance, and HR with practical examples and hypothetical datasets. Predict customer behavior, optimize operations, predict customer credit worthiness, forecast trends, predict employee churn and more!" "Mastering Business Analytics with Python & R: Theory and Practice" revolutionizes data-driven decision-making by seamlessly blending theoretical concepts with hands-on applications, empowering readers to unlock the full potential of Business Analytics across diverse business functions.

Machine Learning For Business Analytics

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Author : Galit Shmueli
language : en
Publisher: John Wiley & Sons
Release Date : 2023-03-22

Machine Learning For Business Analytics written by Galit Shmueli and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-22 with Computers categories.

MACHINE LEARNING FOR BUSINESS ANALYTICS Machine learning —also known as data mining or data analytics— is a fundamental part of data science. It is used by organizations in a wide variety of arenas to turn raw data into actionable information. Machine Learning for Business Analytics: Concepts, Techniques, and Applications in R provides a comprehensive introduction and an overview of this methodology. This best-selling textbook covers both statistical and machine learning algorithms for prediction, classification, visualization, dimension reduction, rule mining, recommendations, clustering, text mining, experimentation, and network analytics. 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 R edition of Machine Learning for Business Analytics. This edition also includes: A new co-author, Peter Gedeck, who brings over 20 years of experience in machine learning using R An expanded chapter focused on discussion of deep learning techniques A new chapter on experimental feedback techniques including A/B testing, uplift modeling, and reinforcement learning A new chapter on responsible data science Updates 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 students A full chapter devoted to relevant case studies with more than a dozen cases demonstrating applications for the machine learning techniques End-of-chapter exercises that help readers gauge and expand their comprehension and competency of the material presented A 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 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.

Practical Business Analytics Using Python And R

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Author : Kumar P
language : en
Publisher: Independently Published
Release Date : 2024-11-22

Practical Business Analytics Using Python And R written by Kumar P and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-22 with Computers categories.

In today's fast-paced and data-driven world, businesses are increasingly relying on data to guide their strategies, optimize operations, and stay ahead of the competition. From customer behavior to market trends, every facet of a business generates vast amounts of data-data that holds the key to better decision-making, enhanced performance, and greater profitability. However, unlocking the potential of this data requires more than just access to it; it requires the tools, techniques, and frameworks that allow us to analyze, interpret, and act on the insights it provides. This book, Practical Business Analytics using Python and R: A Hands-On Approach to Business Intelligence, is designed to provide you with the knowledge and practical skills necessary to leverage the power of data in business contexts. Whether you are a business analyst, data scientist, or business manager, this book aims to equip you with a solid foundation in business analytics using Python and R, one of the most powerful and widely used open-source programming languages for statistical analysis and data science. Python and R have become an indispensable tool in the world of analytics. Its flexibility, vast library of packages, and user-friendly environment make it ideal for analyzing and visualizing data, building predictive models, and uncovering trends that drive business success. In this book, we will guide you through the fundamentals of Python and R, as well as advanced techniques in business analytics, with a focus on solving real-world business problems. Who Should Read This Book? This book is aimed at anyone interested in applying business analytics to solve real-world problems using Python and R. It is ideal for: Business Analysts: Who want to enhance their analytical skills and learn how to use Python and R for solving business problems. Data Scientists: Who are looking to expand their knowledge in business contexts and understand how to apply advanced analytics in a business environment. Managers and Decision Makers: Who want to understand how data-driven insights can inform strategic business decisions. Students and Beginners: Who are learning business analytics, data science, or related fields and want a practical guide to applying analytics using Python and R. This book is structured to cater to both beginners and more advanced users. Each chapter begins with a conceptual introduction to the topic, followed by practical, hands-on examples using Python and R. You will find step-by-step instructions, along with clear explanations of the code and the business implications of the results. Whether you are working through the chapters in order or focusing on specific topics, you will gain the skills necessary to apply business analytics in your organization. So, let's dive in and begin unlocking the true potential of your business data with Python and R!

Big Data Analytics With Python

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Author : Lucas Arden
language : en
Publisher: Independently Published
Release Date : 2025-04-05

Big Data Analytics With Python written by Lucas Arden and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-05 with Computers categories.

Reactive Publishing In Big Data Analytics with Python: Practical Applications for Business, Dr. Lucas Arden delivers a real-world guide for professionals seeking to harness Python's capabilities for data-driven decision-making. Whether you're a business analyst, data scientist, or entrepreneur, this book equips you with practical tools to extract value from complex datasets using Python's most powerful libraries - including Pandas, NumPy, Scikit-learn, and PySpark. Through step-by-step walkthroughs, hands-on coding examples, and real business use cases, you'll learn how to: Clean, transform, and visualize large datasets Apply machine learning to uncover trends and patterns Build predictive models to optimize decision-making Integrate analytics into your business pipeline Solve real business problems with automation and scale Designed for practical application, this guide doesn't just teach you how to code - it teaches you how to think in data. Whether you're scaling a startup or navigating a Fortune 500 enterprise, the skills inside will give you a competitive edge in today's data-driven economy. Turn raw data into revenue - with Python.

Business Analytics With R And Python

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Author : David L. Olson
language : en
Publisher: Springer Nature
Release Date : 2024-07-30

Business Analytics With R And Python written by David L. Olson and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-07-30 with Computers categories.

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.