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Viser: Data Science Foundations Tools and Techniques - Core Skills for Quantitative Analysis with R and Git

Data Science Foundations Tools and Techniques, 1. udgave

Data Science Foundations Tools and Techniques Vital Source e-bog

Michael Freeman og Joel Ross
(2018)
Pearson International
216,00 kr. 194,40 kr.
Leveres umiddelbart efter køb
Data Science Foundations Tools and Techniques, 1. udgave

Data Science Foundations Tools and Techniques Vital Source e-bog

Michael Freeman og Joel Ross
(2018)
Pearson International
254,00 kr. 228,60 kr.
Leveres umiddelbart efter køb
Data Science Foundations Tools and Techniques, 1. udgave

Data Science Foundations Tools and Techniques Vital Source e-bog

Michael Freeman og Joel Ross
(2018)
Pearson International
178,00 kr. 160,20 kr.
Leveres umiddelbart efter køb
Data Science Foundations Tools and Techniques - Core Skills for Quantitative Analysis with R and Git, 1. udgave

Data Science Foundations Tools and Techniques

Core Skills for Quantitative Analysis with R and Git
Michael Freeman og Joel Ross
(2018)
Sprog: Engelsk
Addison Wesley Professional
435,00 kr. 391,50 kr.
ikke på lager, Bestil nu og få den leveret
om ca. 10 hverdage

Detaljer om varen

  • 1. Udgave
  • Vital Source 180 day rentals (dynamic pages)
  • Udgiver: Pearson International (November 2018)
  • Forfattere: Michael Freeman og Joel Ross
  • ISBN: 9780135159088R180
The Foundational Hands-On Skills You Need to Dive into Data Science “Freeman and Ross have created the definitive resource for new and aspiring data scientists to learn foundational programming skills.” –From the foreword by Jared Lander, series editor Using data science techniques, you can transform raw data into actionable insights for domains ranging from urban planning to precision medicine. Programming Skills for Data Science brings together all the foundational skills you need to get started, even if you have no programming or data science experience.   Leading instructors Michael Freeman and Joel Ross guide you through installing and configuring the tools you need to solve professional-level data science problems, including the widely used R language and Git version-control system. They explain how to wrangle your data into a form where it can be easily used, analyzed, and visualized so others can see the patterns you’ve uncovered. Step by step, you’ll master powerful R programming techniques and troubleshooting skills for probing data in new ways, and at larger scales.   Freeman and Ross teach through practical examples and exercises that can be combined into complete data science projects. Everything’s focused on real-world application, so you can quickly start analyzing your own data and getting answers you can act upon. Learn to Install your complete data science environment, including R and RStudio Manage projects efficiently, from version tracking to documentation Host, manage, and collaborate on data science projects with GitHub Master R language fundamentals: syntax, programming concepts, and data structures Load, format, explore, and restructure data for successful analysis Interact with databases and web APIs Master key principles for visualizing data accurately and intuitively Produce engaging, interactive visualizations with ggplot and other R packages Transform analyses into sharable documents and sites with R Markdown Create interactive web data science applications with Shiny Collaborate smoothly as part of a data science team Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.
Licens varighed:
Bookshelf online: 180 dage fra købsdato.
Bookshelf appen: 180 dage fra købsdato.

Udgiveren oplyser at følgende begrænsninger er gældende for dette produkt:
Print: 2 sider kan printes ad gangen
Copy: højest 2 sider i alt kan kopieres (copy/paste)

Detaljer om varen

  • 1. Udgave
  • Vital Source 365 day rentals (dynamic pages)
  • Udgiver: Pearson International (November 2018)
  • Forfattere: Michael Freeman og Joel Ross
  • ISBN: 9780135159088R365
The Foundational Hands-On Skills You Need to Dive into Data Science “Freeman and Ross have created the definitive resource for new and aspiring data scientists to learn foundational programming skills.” –From the foreword by Jared Lander, series editor Using data science techniques, you can transform raw data into actionable insights for domains ranging from urban planning to precision medicine. Programming Skills for Data Science brings together all the foundational skills you need to get started, even if you have no programming or data science experience.   Leading instructors Michael Freeman and Joel Ross guide you through installing and configuring the tools you need to solve professional-level data science problems, including the widely used R language and Git version-control system. They explain how to wrangle your data into a form where it can be easily used, analyzed, and visualized so others can see the patterns you’ve uncovered. Step by step, you’ll master powerful R programming techniques and troubleshooting skills for probing data in new ways, and at larger scales.   Freeman and Ross teach through practical examples and exercises that can be combined into complete data science projects. Everything’s focused on real-world application, so you can quickly start analyzing your own data and getting answers you can act upon. Learn to Install your complete data science environment, including R and RStudio Manage projects efficiently, from version tracking to documentation Host, manage, and collaborate on data science projects with GitHub Master R language fundamentals: syntax, programming concepts, and data structures Load, format, explore, and restructure data for successful analysis Interact with databases and web APIs Master key principles for visualizing data accurately and intuitively Produce engaging, interactive visualizations with ggplot and other R packages Transform analyses into sharable documents and sites with R Markdown Create interactive web data science applications with Shiny Collaborate smoothly as part of a data science team Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.
Licens varighed:
Bookshelf online: 5 år fra købsdato.
Bookshelf appen: 5 år fra købsdato.

Udgiveren oplyser at følgende begrænsninger er gældende for dette produkt:
Print: 2 sider kan printes ad gangen
Copy: højest 2 sider i alt kan kopieres (copy/paste)

Detaljer om varen

  • 1. Udgave
  • Vital Source 90 day rentals (dynamic pages)
  • Udgiver: Pearson International (November 2018)
  • Forfattere: Michael Freeman og Joel Ross
  • ISBN: 9780135159088R90
The Foundational Hands-On Skills You Need to Dive into Data Science “Freeman and Ross have created the definitive resource for new and aspiring data scientists to learn foundational programming skills.” –From the foreword by Jared Lander, series editor Using data science techniques, you can transform raw data into actionable insights for domains ranging from urban planning to precision medicine. Programming Skills for Data Science brings together all the foundational skills you need to get started, even if you have no programming or data science experience.   Leading instructors Michael Freeman and Joel Ross guide you through installing and configuring the tools you need to solve professional-level data science problems, including the widely used R language and Git version-control system. They explain how to wrangle your data into a form where it can be easily used, analyzed, and visualized so others can see the patterns you’ve uncovered. Step by step, you’ll master powerful R programming techniques and troubleshooting skills for probing data in new ways, and at larger scales.   Freeman and Ross teach through practical examples and exercises that can be combined into complete data science projects. Everything’s focused on real-world application, so you can quickly start analyzing your own data and getting answers you can act upon. Learn to Install your complete data science environment, including R and RStudio Manage projects efficiently, from version tracking to documentation Host, manage, and collaborate on data science projects with GitHub Master R language fundamentals: syntax, programming concepts, and data structures Load, format, explore, and restructure data for successful analysis Interact with databases and web APIs Master key principles for visualizing data accurately and intuitively Produce engaging, interactive visualizations with ggplot and other R packages Transform analyses into sharable documents and sites with R Markdown Create interactive web data science applications with Shiny Collaborate smoothly as part of a data science team Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.
Licens varighed:
Bookshelf online: 90 dage fra købsdato.
Bookshelf appen: 90 dage fra købsdato.

Udgiveren oplyser at følgende begrænsninger er gældende for dette produkt:
Print: 2 sider kan printes ad gangen
Copy: højest 2 sider i alt kan kopieres (copy/paste)

Detaljer om varen

  • 1. Udgave
  • Paperback: 384 sider
  • Udgiver: Addison Wesley Professional (November 2018)
  • Forfattere: Michael Freeman og Joel Ross
  • ISBN: 9780135133101

The Foundational Hands-On Skills You Need to Dive into Data Science

"Freeman and Ross have created the definitive resource for new and aspiring data scientists to learn foundational programming skills."

-From the foreword by Jared Lander, series editor

Using data science techniques, you can transform raw data into actionable insights for domains ranging from urban planning to precision medicine. Programming Skills for Data Science brings together all the foundational skills you need to get started, even if you have no programming or data science experience.

 

Leading instructors Michael Freeman and Joel Ross guide you through installing and configuring the tools you need to solve professional-level data science problems, including the widely used R language and Git version-control system. They explain how to wrangle your data into a form where it can be easily used, analyzed, and visualized so others can see the patterns you've uncovered. Step by step, you'll master powerful R programming techniques and troubleshooting skills for probing data in new ways, and at larger scales.

 

Freeman and Ross teach through practical examples and exercises that can be combined into complete data science projects. Everything's focused on real-world application, so you can quickly start analyzing your own data and getting answers you can act upon. Learn to

  • Install your complete data science environment, including R and RStudio
  • Manage projects efficiently, from version tracking to documentation
  • Host, manage, and collaborate on data science projects with GitHub
  • Master R language fundamentals: syntax, programming concepts, and data structures
  • Load, format, explore, and restructure data for successful analysis
  • Interact with databases and web APIs
  • Master key principles for visualizing data accurately and intuitively
  • Produce engaging, interactive visualizations with ggplot and other R packages
  • Transform analyses into sharable documents and sites with R Markdown
  • Create interactive web data science applications with Shiny
  • Collaborate smoothly as part of a data science team

Register your book for convenient access to downloads, updates, and/or corrections as they become available. See inside book for details.


Part I: Getting Started
Chapter 1: Setting Up Your Computer
Chapter 2: Using the Command Line
Part II: Managing Projects
Chapter 3: Version Control with git and GitHub
Chapter 4: Using Markdown for Documentation
Part III: Foundational R Skills
Chapter 5: Introduction to R
Chapter 6: Functions
Chapter 7: Vectors
Chapter 8: Lists
Part IV: Data Wrangling
Chapter 9: Understanding Data
Chapter 10: Data Frames
Chapter 11: Manipulating Data with dplyr
Chapter 12: Reshaping Data with tidyr
Chapter 13: Accessing Databases
Chapter 14: Accessing Web APIs
Part V: Data Visualization
Chapter 15: Designing Data Visualizations
Chapter 16: Creating Visualizations with ggplot2
Chapter 17: Interactive Visualization in R
Part VI: Building and Sharing Applications
Chapter 18: Dynamic Reports with R Markdown
Chapter 19: Building Interactive Web Applications with Shiny
Chapter 20: Working Collaboratively
Chapter 21: Moving Forward Index
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