Everything about the Book
The Book
Please order the book on the publisher’s page. On this page, you will find more information about the book. Description of the book from the publisher’s website:
Data Science in Practice is the ideal introduction to data science. With or without math skills, here, you get the all-round view that you need for your projects. This book describes how to properly question data, in order to unearth the treasure that data can be. You will get to know the relevant analysis methods, and will be introduced to the programming language R, which is ideally suited for data analysis. Associated tools like notebooks that make data science programming easily accessible are included in this introduction. Because technology alone is not enough, this book also deals with problems in project implementation, illuminates various fields of application, and does not forget to address ethical aspects. Data Science in Practice includes many examples, notes on errors, decision-making aids, and other practical tips. This book is ideal as a complementary text for university students, and is a useful learning tool for those moving into more data-related roles.
GitHub Repository
Errata
none
Links in the Book
- Introduction
- Machine Learning, Data Science, and Artificial Intelligence
- Data Science Projects
- Introduction to R
- R Download
- Mac page of the R Projekts
- Download RStudio
- AOL Search Scandal in the New York Times
- R Styleguide
- Open Source Alternative to SPSS: PSPP
- Julia
- Popularity of R in Science
- CRAN – Comprehensive R Archive Network
- R Foundation
- R Consortium
- Explorative Data Analysis
- An EDA about Data Science und SEO
- What are Tibbles?
- Cheat Sheet for regular expressions in R
- Scientists cannot explain the p value
- Predictions
- no links
- Clustering
- Classification
- Other Applications
- After the model
- Happy Git with R
- RStudio AMIs by Louis Aslett
- data.table
- plumber Package zum Erstellen von APIs
- docker Image including plumber
- My Corona-Dashboard, built with Shiny, https://alby.link/coronashinygithub.
- Data Protection
- After this book
- Stackoverflow Sites
- R Mailing list
- R-Seek, a search engine for R resources
- Appendix
- Typical Error Messages
- Glossary