Data Science
A First Introduction
(Sprache: Englisch)
Data Science: An Introduction focuses on using the R programming language in Jupyter notebooks to perform basic data manipulation and cleaning, create effective visualizations, and extract insights from data using supervised predictive models.
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Data Science: An Introduction focuses on using the R programming language in Jupyter notebooks to perform basic data manipulation and cleaning, create effective visualizations, and extract insights from data using supervised predictive models.
Inhaltsverzeichnis zu „Data Science “
1. R and the tidyverse, 2. Reading in data locally and from the web, 3. Cleaning and wrangling data, 4. Effective data visualization, 5. Classification I: training & predicting, 6. Classification II: evaluation & tuning, 7. Regression I: K-nearest neighbors, 8. Regression II: linear regression, 9. Clustering, 10. Statistical inference, 11. Combining code and text with Jupyter, 12. Collaboration with version control, 13. Setting up your computer
Autoren-Porträt von Tiffany Timbers, Trevor Campbell, Melissa Lee
Tiffany Timbers is an Assistant Professor of Teaching in the Department of Statistics and Co-Director for the Master of Data Science program (Vancouver Option) at the University of British Columbia.Trevor Campbell is an Assistant Professor in the Department of Statistics at the University of British Columbia.
Melissa Lee is an Assistant Professor of Teaching in the Department of Statistics at the University of British Columbia
Bibliographische Angaben
- Autoren: Tiffany Timbers , Trevor Campbell , Melissa Lee
- 2022, 456 Seiten, mit farbigen Abbildungen, Maße: 17,4 x 24,8 cm, Taschenbuch, Englisch
- Verlag: Taylor & Francis
- ISBN-10: 0367524686
- ISBN-13: 9780367524685
- Erscheinungsdatum: 15.07.2022
Sprache:
Englisch
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