Название: Open Source Software for Statistical Analysis of Big dаta: Emerging Research and Opportunities
Автор: Richard S. Segall, Gao Niu
Издательство: IGI Global
Год: 2020
Страниц: 252
Язык: английский
Формат: pdf (true), epub
Размер: 16.9 MB, 33.4 MB

With the development of computing technologies in todays modernized world, software packages have become easily accessible. Open source software, specifically, is a popular method for solving certain issues in the field of computer science. One key challenge is analyzing big data due to the high amounts that organizations are processing. Researchers and professionals need research on the foundations of open source software programs and how they can successfully analyze statistical data.

Open Source Software for Statistical Analysis of Big dаta: Emerging Research and Opportunities provides emerging research exploring the theoretical and practical aspects of cost-free software possibilities for applications within data analysis and statistics with a specific focus on R and Python. Featuring coverage on a broad range of topics such as cluster analysis, time series forecasting, and Machine Learning (ML), this book is ideally designed for researchers, developers, practitioners, engineers, academicians, scholars, and students who want to more fully understand in a brief and concise format the realm and technologies of open source software for Big Data and how it has been used to solve large-scale research problems in a multitude of disciplines.

Topics Covered:

The many academic areas covered in this publication include, but are not limited to:

Cluster Analysis
Data Analytics
Data Visualization
Fatality Rate Modeling
High Performance Computing
Machine Learning
Neural Networks
Python
R Programming
Statistical Coding
Time Series Forecasting











[related-news] [/related-news]