Data Science: A First Introduction
Tiffany Timbers, Trevor Campbell, Melissa Lee
Data Science: A First Introduction focuses on using the R programming language in Jupyter notebooks to perform data manipulation and cleaning, create effective visualizations, and extract insights from data using classification, regression, clustering, and inference. The text emphasizes workflows that are clear, reproducible, and shareable, and includes coverage of the basics of version control. All source code is available online, demonstrating the use of good reproducible project workflows. Based on educational research and active learning principles, the book uses a modern approach to R and includes accompanying autograded Jupyter worksheets for interactive, self-directed learning. The book will leave readers well-prepared for data science projects. The book is designed for learners from all disciplines with minimal prior knowledge of mathematics and programming. The authors have honed the material through years of experience teaching thousands of undergraduates in the University of British Columbia's DSCI100: Introduction to Data Science course.
Categorías:
Año:
2022
Edición:
1
Editorial:
Chapman and Hall/CRC
Idioma:
english
Páginas:
456
ISBN 10:
0367532174
ISBN 13:
9780367532178
Serie:
Chapman & Hall/CRC Data Science Series
Archivo:
PDF, 53.00 MB
IPFS:
,
english, 2022