Practical Business Analytics Using Python And R

DOWNLOAD

Download Practical Business Analytics Using Python And R PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Practical Business Analytics Using Python And R book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page

Business Analytics Using R A Practical Approach

DOWNLOAD
Author : Umesh R Hodeghatta
language : en
Publisher: Apress
Release Date : 2016-12-27

Business Analytics Using R A Practical Approach written by Umesh R Hodeghatta and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-27 with Computers categories.

Learn the fundamental aspects of the business statistics, data mining, and machine learning techniques required to understand the huge amount of data generated by your organization. This book explains practical business analytics through examples, covers the steps involved in using it correctly, and shows you the context in which a particular technique does not make sense. Further, Practical Business Analytics using R helps you understand specific issues faced by organizations and how the solutions to these issues can be facilitated by business analytics. This book will discuss and explore the following through examples and case studies: An introduction to R: data management and R functions The architecture, framework, and life cycle of a business analytics project Descriptive analytics using R: descriptive statistics and data cleaning Data mining: classification, association rules, and clustering Predictiveanalytics: simple regression, multiple regression, and logistic regression This book includes case studies on important business analytic techniques, such as classification, association, clustering, and regression. The R language is the statistical tool used to demonstrate the concepts throughout the book. What You Will Learn • Write R programs to handle data • Build analytical models and draw useful inferences from them • Discover the basic concepts of data mining and machine learning • Carry out predictive modeling • Define a business issue as an analytical problem Who This Book Is For Beginners who want to understand and learn the fundamentals of analytics using R. Students, managers, executives, strategy and planning professionals, software professionals, and BI/DW professionals.

Practical Business Analytics Using Python And R

DOWNLOAD
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!

Practical Business Analytics Using R And Python

DOWNLOAD
Author : Umesh R. Hodeghatta
language : en
Publisher:
Release Date : 2023

Practical Business Analytics Using R And Python written by Umesh R. Hodeghatta and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with categories.

This book illustrates how data can be useful in solving business problems. It explores various analytics techniques for using data to discover hidden patterns and relationships, predict future outcomes, optimize efficiency and improve the performance of organizations. You'll learn how to analyze data by applying concepts of statistics, probability theory, and linear algebra. In this new edition, both R and Python are used to demonstrate these analyses. Practical Business Analytics Using R and Python also features new chapters covering databases, SQL, Neural networks, Text Analytics, and Natural Language Processing. Part one begins with an introduction to analytics, the foundations required to perform data analytics, and explains different analytics terms and concepts such as databases and SQL, basic statistics, probability theory, and data exploration. Part two introduces predictive models using statistical machine learning and discusses concepts like regression, classification, and neural networks. Part three covers two of the most popular unsupervised learning techniques, clustering and association mining, as well as text mining and natural language processing (NLP). The book concludes with an overview of big data analytics, R and Python essentials for analytics including libraries such as pandas and NumPy. Upon completing this book, you will understand how to improve business outcomes by leveraging R and Python for data analytics. You will: Master the mathematical foundations required for business analytics Understand various analytics models and data mining techniques such as regression, supervised machine learning algorithms for modeling, unsupervised modeling techniques, and how to choose the correct algorithm for analysis in any given task Use R and Python to develop descriptive models, predictive models, and optimize models Interpret and recommend actions based on analytical model outcomes.

Mastering Business Analytics With Python R

DOWNLOAD
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.

Business Analytics

DOWNLOAD
Author : Walter R. Paczkowski
language : en
Publisher: Springer Nature
Release Date : 2022-01-03

Business Analytics written by Walter R. Paczkowski and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-03 with Business & Economics categories.

This book focuses on three core knowledge requirements for effective and thorough data analysis for solving business problems. These are a foundational understanding of: 1. statistical, econometric, and machine learning techniques; 2. data handling capabilities; 3. at least one programming language. Practical in orientation, the volume offers illustrative case studies throughout and examples using Python in the context of Jupyter notebooks. Covered topics include demand measurement and forecasting, predictive modeling, pricing analytics, customer satisfaction assessment, market and advertising research, and new product development and research. This volume will be useful to business data analysts, data scientists, and market research professionals, as well as aspiring practitioners in business data analytics. It can also be used in colleges and universities offering courses and certifications in business data analytics, data science, and market research.

Structure And Structural Change In China S Economy

DOWNLOAD
Author : Dong Guo
language : en
Publisher:
Release Date : 2005

Structure And Structural Change In China S Economy written by Dong Guo and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with China categories.

Business Analytics With Python

DOWNLOAD
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.

Business Analytics Using Python

DOWNLOAD
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!

Dr Dobb S Journal

DOWNLOAD
Author :
language : en
Publisher:
Release Date : 2005

Dr Dobb S Journal written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Application software categories.

Data Mining For Business Analytics

DOWNLOAD
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.