Data Science in R: A Case Studies Approach to Computational Reasoning and Problem Solving (Chapman & Hall/CRC The R Series) - Tapa blanda

Libro 16 de 73: Chapman & Hall/CRC The R

Nolan, Deborah; Lang, Duncan Temple

 
9781482234817: Data Science in R: A Case Studies Approach to Computational Reasoning and Problem Solving (Chapman & Hall/CRC The R Series)
Tapa blanda
ISBN 10: 1482234815 ISBN 13: 9781482234817
Editorial: Chapman and Hall/CRC, 2015

Sinopsis

Effectively Access, Transform, Manipulate, Visualize, and Reason about Data and Computation

Data Science in R: A Case Studies Approach to Computational Reasoning and Problem Solving illustrates the details involved in solving real computational problems encountered in data analysis. It reveals the dynamic and iterative process by which data analysts approach a problem and reason about different ways of implementing solutions.

The book’s collection of projects, comprehensive sample solutions, and follow-up exercises encompass practical topics pertaining to data processing, including:

  • Non-standard, complex data formats, such as robot logs and email messages
  • Text processing and regular expressions
  • Newer technologies, such as Web scraping, Web services, Keyhole Markup Language (KML), and Google Earth
  • Statistical methods, such as classification trees, k-nearest neighbors, and naïve Bayes
  • Visualization and exploratory data analysis
  • Relational databases and Structured Query Language (SQL)
  • Simulation
  • Algorithm implementation
  • Large data and efficiency

Suitable for self-study or as supplementary reading in a statistical computing course, the book enables instructors to incorporate interesting problems into their courses so that students gain valuable experience and data science skills. Students learn how to acquire and work with unstructured or semistructured data as well as how to narrow down and carefully frame the questions of interest about the data.

Blending computational details with statistical and data analysis concepts, this book provides readers with an understanding of how professional data scientists think about daily computational tasks. It will improve readers’ computational reasoning of real-world data analyses.

"Sinopsis" puede pertenecer a otra edición de este libro.

Acerca del autor

Deborah Nolan holds the Zaffaroni Family Chair in Undergraduate Education at the University of California, Berkeley. She is a fellow of the American Statistical Association and the Institute of Mathematical Statistics. Her research has involved the empirical process, high-dimensional modeling, and, more recently, technology in education and reproducible research. Duncan Temple Lang is the director of the Data Science Initiative at the University of California, Davis. He has been involved in the development of R and S for 20 years and has developed over 100 R packages. His research focuses on statistical computing, data technologies, meta-computing, reproducibility, and visualization.

"Sobre este título" puede pertenecer a otra edición de este libro.

Editorial
Chapman and Hall/CRC
Año de publicación
2015
Idioma
Inglés
ISBN 10 
1482234815
ISBN 13 
9781482234817
Encuadernación
Tapa blanda
Número de edición
1
Número de páginas
540
Contacto del fabricante
Taylor and Francis, GPSR Taylor and Francis
gpsr@taylorandfrancis.com

Taylor & Francis Verlag GmbH, Kaufingerstraße 24
München
80331
Alemania

Otras ediciones populares con el mismo título

9781138469297: Data Science in R: A Case Studies Approach to Computational Reasoning and Problem Solving (Chapman & Hall/CRC The R Series)

Edición Destacada

ISBN 10:  1138469297 ISBN 13:  9781138469297
Editorial: Chapman and Hall/CRC, 2017
Tapa dura