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Modern Data Science with R
Langbeschreibung
This textbook is designed for an undergraduate course in data science that emphasizes topics in both statistics and computer science.
Inhaltsverzeichnis
I Part I: Introduction to Data Science. 1. Prologue: Why data science? 2. Data visualization. 3. A grammar for graphics. 4. Data wrangling on one table. 5. Data wrangling on multiple tables. 6. Tidy data. 7. Iteration. 8. Data science ethics. II. Part II: Statistics and Modeling. 9. Statistical foundations. 10. Predictive modeling. 11. Supervised learning. 12. Unsupervised learning. 13. Simulation. III Part III: Topics in Data Science. 14. Dynamic and customized data graphics. 15. Database querying using SQL. 16. Database administration. 17. Working with spatial data. 18.Geospatial computations. 19. Text as data. 20. Network science. IV Part IV: Appendices.
Benjamin S. Baumer is an associate professor in the Statistical & Data Sciences program at Smith College. He has been a practicing data scientist since 2004, when he became the first full-time statistical analyst for the New York Mets. Ben is a co-author of The Sabermetric Revolution and Analyzing Baseball Data with R. He received the 2019 Waller Education Award and the 2016 Significant Contributor Award from the Society for American Baseball Research.
ISBN-13:
9780429577505
Veröffentl:
2021
Seiten:
650
Autor:
Benjamin S. Baumer
eBook Typ:
PDF
eBook Format:
EPUB
Kopierschutz:
0 - No protection
Sprache:
Englisch
114,99 €*
Lieferzeit: Sofort lieferbar
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