Open Source Software for Statistical Analysis of Big Data by Richard S Segall
With the development of computing technologies in today's 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.-
5G Internet of Things and Changing Standards for Computing and Electronic Systems
-
Hydrogen Fuel Cell Technology for Stationary Applications
-
Innovations in the Industrial Internet of Things (IIoT) and Smart Factory
-
Handbook of Research on AI Methods and Applications in Computer Engineering
-
IoT Architectures, Models, and Platforms for Smart City Applications
-
Handbook of Research on 5G Networks and Advancements in Computing, Electronics, and Electrical Engineering
-
Tools and Technologies for the Development of Cyber-Physical Systems
-
Innovative Applications of Nanowires for Circuit Design
-
Pattern Recognition Applications in Engineering
-
Computational Methodologies for Electrical and Electronics Engineers
-
Emerging Applications of Fuzzy Algebraic Structures
-
Advanced Applications of Fractional Differential Operators to Science and Technology
-
Optimizing and Measuring Smart Grid Operation and Control
-
Machine Learning for Environmental Monitoring in Wireless Sensor Networks
-
Edible Electronics for Smart Technology Solutions
-
Developing Digital Inclusion Through Globalization and Digitalization
-
Nature-Inspired Optimization Algorithms for Cyber-Physical Systems
-
Emerging Trends in Cloud Computing Analytics, Scalability, and Service Models
-
Driving Transformative Technology Trends With Cloud Computing
-
Navigating the Augmented and Virtual Frontiers in Engineering
-
Impact and Potential of Machine Learning in the Metaverse
-
Harnessing Green and Circular Skills for Digital Transformation
-
Battery-Free Sensor Networks for Sustainable Next-Generation IoT Connectivity
-
Advancing Intelligent Networks Through Distributed Optimization
-
Digital Technologies for Sustainability and Quality Control
-
Navigating Cyber-Physical Systems With Cutting-Edge Technologies
-
Modern SuperHyperSoft Computing Trends in Science and Technology
-
Multifaceted Uses of Cutting-Edge Technologies and Social Concerns
-
Machine Learning and Deep Learning in Real-Time Applications
-
Handbook of Research on Engineering Innovations and Technology Management in Organizations
-
Research Advancements in Smart Technology, Optimization, and Renewable Energy
-
Principles and Theories of Data Mining With RapidMiner
-
Industrial Internet of Things and Cyber-Physical Systems
-
Energy Systems Design for Low-Power Computing
-
Structural and Functional Aspects of Biocomputing Systems for Data Processing
| SKU | Unavailable |
| ISBN 13 | 9781799827689 |
| ISBN 10 | 1799827682 |
| Title | Open Source Software for Statistical Analysis of Big Data |
| Author | Richard S Segall |
| Series | Advances In Computer And Electrical Engineering Ser |
| Condition | Unavailable |
| Binding Type | Hardback |
| Publisher | IGI Global |
| Year published | 2020-01-30 |
| Number of pages | 250 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |