Beginning data science in R 4 data analysis, visualization, and modelling for the data scientist
Discover best practices for data analysis and software development in R and start on the path to becoming a fully-fledged data scientist. Updated for the R 4.0 release, this book teaches you techniques for both data manipulation and visualization and shows you the best way for developing new softwar...
| Otros Autores: | |
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| Formato: | Libro electrónico |
| Idioma: | Inglés |
| Publicado: |
New York, NY :
Apress Media, LLC
[2022]
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| Edición: | Second edition |
| Materias: | |
| Ver en Biblioteca Universitat Ramon Llull: | https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009668677006719 |
Tabla de Contenidos:
- 1: Introduction 2: Introduction to R Programming 3: Reproducible Analysis 4: Data Manipulation 5: Visualizing Data 6: Working with Large Data Sets 7: Supervised Learning 8: Unsupervised Learning 9: Project 1: Hitting the Bottle 10: Deeper into R Programming 11: Working with Vectors and Lists 12: Functional Programming 13: Object-Oriented Programming 14: Building an R Package 15: Testing and Package Checking 16: Version Control 17: Profiling and Optimizing 18: Project 2: Bayesian Linear Progression 19: Conclusions
