Название: Business Analytics with R and Python
Автор: David L. Olson, Desheng Dash Wu, Cuicui Luo, Majid Nabavi
Издательство: Springer
Серия: AI for Risks
Год: 2024
Страниц: 201
Язык: английский
Формат: pdf (true), epub
Размер: 42.5 MB

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 (AI) 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.

R is a command line software. R Studio, a Graphical User Interface (GUI) and integrated programming environment developed for R, provides a user-friendly programming environment by making screen menus for packages, functions, and files, surfing and saving utilities, and concurrent access to multiple scripts, files, and directories. R packages provide pre-programmed functions for a variety of analytical processes. These functions are only available to programmers if their library is already loaded into the working space. For example, ggplot() function will not work unless the library ggplot2 is loaded prior to call for this function: library(ggplot2). Loading all libraries required for a script first, is a good practice. These libraries need to be installed prior to loading too. R will download on computers with basic functionality. Thousands of additional libraries however, are available for download. We can download them using either the command line or RStudio menu.

Python is also a command line programming language. Python base is a limited library, available to download with a standard command line editor. A note states that Python version above 3.9 cannot be used on Windows 7 or earlier. Python is available for various operating systems like Windows, macOS, and Linux. Choose the installer that corresponds to your operating system. For example, if you're using Windows, download the Windows installer. If you're using macOS, download the macOS installer. A number of other editors have been developed for Python programming, among them Jupyter notebook is a popular tool. Jupyter and a number of other programming tools are packaged in Anaconda suite. An advantage of Anaconda suite is providing a Python distribution that includes many additional libraries, eliminating the need for finding, downloading, and install them as required in basic editors.








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