Readings & Resources
Reading List
- Christopher M. Bishop: Pattern Recognition and Machine Learning; Springer, 2007 - Website
- Han, Kamber: Data Mining: Concepts and Techniques; Elsevier, 2012 - Website
- Hastie, Tibshirani, Friedman: The Elements of Statistical Learning; Springer, 2009 - Website
- James, Witten, Hastie, Tibshirani: An Introduction to Statistical Learning with Applications in R; Springer, 2015 - Website
- Tan, Steinbach, Kumar: Introduction to Data Mining; Pearson, 2005 - Website
Introductory Readings
- Fahrmeier, Künstler, Pigeot, Tutz: Statistik: Der Weg zur Datenanalyse; Springer, 2016 - Website
- Maindonald, Braun: Data Analysis and Graphics Using R - An Example-Based Approach; Cambridge University Press, 2010 - Website
- Rice: Mathematical Statistics and Data Analysis; Duxbury Advanced, 2007 - Website
Books on R
- Davies: Book of R - A First Course in Programming and Statistics; No Starch Press, 2016 - Website
- Matloff: Art of R Programming - A Tour of Statistical Software Design; No Starch Press, 2011 - Website
- Wickham: R for Data Science; O'Reilly Media, 2016 - Website
- Wickham: R Packages; O'Reilly Media, 2015 - Website
- Wickham: Advanced R; Chapman & Hall/CRC The R Series, 2014 - Website
Resources
- Kaggle - Website
- CRAN - The Comprehensive R Archive Network - Website
- MRAN - Microsoft R Application Network - Website
- RStudio - Website
- RStudio Cheat Sheets - link
- RStudio Online Courses - link
- useR! 2016 talks - link
- Visualizations of Probability Concepts - link