Data science in R a case studies approach to computational reasoning and problem solving
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.
Main Authors: | , |
---|---|
Format: | Texto biblioteca |
Language: | eng |
Published: |
Boca Raton, FL CRC Press Taylor & Francis Group
c201
|
Subjects: | R (Lenguaje de programación para computadora), Métodos estadísticos, Procesamiento de datos, |
Online Access: | http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=974058 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
id |
KOHA-OAI-ECOSUR:57774 |
---|---|
record_format |
koha |
institution |
ECOSUR |
collection |
Koha |
country |
México |
countrycode |
MX |
component |
Bibliográfico |
access |
En linea En linea |
databasecode |
cat-ecosur |
tag |
biblioteca |
region |
America del Norte |
libraryname |
Sistema de Información Bibliotecario de ECOSUR (SIBE) |
language |
eng |
topic |
R (Lenguaje de programación para computadora) Métodos estadísticos Procesamiento de datos R (Lenguaje de programación para computadora) Métodos estadísticos Procesamiento de datos |
spellingShingle |
R (Lenguaje de programación para computadora) Métodos estadísticos Procesamiento de datos R (Lenguaje de programación para computadora) Métodos estadísticos Procesamiento de datos Nolan, Deborah autor/a Lang, Duncan Temple autor/a Data science in R a case studies approach to computational reasoning and problem solving |
description |
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. |
format |
Texto |
topic_facet |
R (Lenguaje de programación para computadora) Métodos estadísticos Procesamiento de datos |
author |
Nolan, Deborah autor/a Lang, Duncan Temple autor/a |
author_facet |
Nolan, Deborah autor/a Lang, Duncan Temple autor/a |
author_sort |
Nolan, Deborah autor/a |
title |
Data science in R a case studies approach to computational reasoning and problem solving |
title_short |
Data science in R a case studies approach to computational reasoning and problem solving |
title_full |
Data science in R a case studies approach to computational reasoning and problem solving |
title_fullStr |
Data science in R a case studies approach to computational reasoning and problem solving |
title_full_unstemmed |
Data science in R a case studies approach to computational reasoning and problem solving |
title_sort |
data science in r a case studies approach to computational reasoning and problem solving |
publisher |
Boca Raton, FL CRC Press Taylor & Francis Group |
publishDate |
c201 |
url |
http://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=974058 |
work_keys_str_mv |
AT nolandeborahautora datascienceinracasestudiesapproachtocomputationalreasoningandproblemsolving AT langduncantempleautora datascienceinracasestudiesapproachtocomputationalreasoningandproblemsolving |
_version_ |
1756228279665164289 |
spelling |
KOHA-OAI-ECOSUR:577742021-01-11T22:04:18ZData science in R a case studies approach to computational reasoning and problem solving Nolan, Deborah autor/a Lang, Duncan Temple autor/a textBoca Raton, FL CRC Press Taylor & Francis Groupc2015engEffectively 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.Incluye bibliografía e índice: páginas 507-513Effectively 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.Disponible en formato PDFSubscripción a EBSCOhostR (Lenguaje de programación para computadora)Métodos estadísticosProcesamiento de datosDisponible en líneaData science in R: a case studies approach to computational reasoning and problem solvinghttp://search.ebscohost.com/login.aspx?direct=true&scope=site&db=nlebk&db=nlabk&AN=974058URN:ISBN:1482234815URN:ISBN:9781482234817Disponible para usuarios de ECOSUR con su clave de acceso |