Open Source Software for Statistical Ana
β Segall Richard
π Library
π
2020
π Engineering Science Reference
π English
β¦ LIBER β¦
π
Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities
β Scribed by Richard S. Segall, Gao Niu
- Publisher
- IGI Global
- Year
- 2020
- Tongue
- English
- Leaves
- 252
- Edition
- 1
- Category
- Library
β¬ Acquire This Volume
No coin nor oath required. For personal study only.
β¦ Synopsis
https://www.igi-global.com/book/237841
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 Data: 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, 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.
β¦ Table of Contents
Cover
Title Page
Copyright Page
Book Series
Editorial Advisory Board and List of Reviewers
Table of Contents
Preface
Acknowledgment
Chapter 1: What Is Open Source Software (OSS) and What Is Big Data?
Chapter 2: Open Source Software (OSS) for Big Data
Chapter 3: Introduction to the Popular Open Source Statistical Software (OSSS)
Chapter 4: Cluster Analysis in R With Big Data Applications
Chapter 5: Generalized Linear Model for Automobile Fatality Rate Prediction in R
Chapter 6: Introduction to Python and Its Statistical Applications
Chapter 7: A Comparison of Machine Learning Algorithms of Big Data for Time Series Forecasting Using Python
Conclusion
Related Readings
About the Contributors
Index
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