Beginning Data Science in R Data Analysis, Visualization, and Modelling for the Data Scientist /

• Main Author: Mailund, Thomas (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic eBook
• Language: English
• Published: Berkeley, CA : Apress : Imprint: Apress, 2017.
• Subjects: Computer science.; Computer programming.; Programming languages (Electronic computers).; Data mining.; Computer Science.; Data Mining and Knowledge Discovery.; Big Data.; Programming Languages, Compilers, Interpreters.; Data-driven Science, Modeling and Theory Building.; Programming Techniques.

Discover best practices for data analysis and software development in R and start on the path to becoming a fully-fledged data scientist. This book teaches you techniques for both data manipulation and visualization and shows you the best way for developing new software packages for R. Data Science...

Table of Contents:

• 1. Introduction to R programming
• 2. Reproducible analysis
• 3. Data manipulation
• 4. Visualizing and exploring data
• 5. Working with large data sets
• 6. Supervised learning
• 7. Unsupervised learning
• 8. More R programming
• 9. Advanced R programming
• 10. Object oriented programming
• 11. Building an R package
• 12. Testing and checking
• 13. Version control
• 14. Profiling and optimizing.