Bookmarks_References

Just useful References!

R

• R - The R Project for Statistical Computing
• Revolution Analytics
  • Note: Revolution R Open is now known as Microsoft R Open (MRO). Download Link
• RStudio
  • Best IDE for R Language.
• Bioconductor - Open Source Software For Bioinformatics
• rseek

Python

• Python - Official Site
• Continuum - Anaconda
  • Python IDEs
    • Spyder IDE
    • PyCharm Community Edition
    • Rodeo by yhat

Learning R Online

• DataCamp
• dataquest
• Code School - try R
• LEADA
• swirl - Learn R, in R
• RStudio - Webinars and Videos On Demand
• simplilearn
• R by example

Learning Data Science Online

• udemy - by Charles Redmond, Professor at Mercyhurst University
  1. R, ggplot, and Simple Linear Regression
  2. Polynomial Regression, R, and ggplot
  3. Training Sets, Test Sets, R, and ggplot
  4. Baseball Database Queries with SQL and dplyr
  5. Baseball Data Wrangling with Vagrant, R, and Retrosheet
  6. Pitch Location Charts with PITCHf/x and ggplot
  7. Batting Location Charts with Vagrant and MySQL
• Explore Statistics with R by Karolinska Institutet
• Springboard -- There are many wokshops that related to Data Science
• Data Sci Guide

Data Science Competitions

• Kaggle
• DrivenData
• CrowdANALYTIX
• InnoCentive

Data Repositories

• UC Irvine Machine Learning Repository

Blogs and Websites for Data Science

• R-bloggers
• r-dir
• inside-R
• R-statistics
• Data Mining, Analytics, Big Data, and Data Science - KDnuggets
• Analytics Vidhya
• Data Science Central
• Predictive Analytics World
• r-statistics.co: An educational resource for those seeking knowledge related to machine learning and statistical computing in R.
• R for Public Health
• ZevRoss - Know Your Data
• SIMPLY STATISTICS - simplystats
• Statistical Modeling, Causal Inference, and Social Science
• Statistics.com
• pythonprogramming.net -- mainly using PYTHON -- INCLUDING VIDEOS
• ParallelR blog

Book Reviews

• rkbookreviews

Books

Books in R / Using R

1. The Elements of Statistical Learning: Data Mining, Inference, and Prediction by Trevor Hastie, Robert Tibshirani, and Jerome Friedman
2. An Introduction to Statistical Learning with Applications in R
   by Gareth James, Daniela Witten, Trevor Hastie, and Robert Tibshirani
3. R Programming for Data Science by Roger D. Peng
4. The Art of Data Science by Roger D. Peng AND Elizabeth Matsui
5. Exploratory Data Analysis with R by Roger D. Peng
6. Report Writing for Data Science in R by Roger D. Peng
7. Statistical inference for data science by Brian Caffo
8. Regression Models for Data Science in R by Brian Caffo
9. Advanced Linear Models for Data Science by Brian Caffo
10. Developing Data Products in R by Brian Caffo
11. The Elements of Data Analytic Style by Jeff Leek
12. Learning Statistics with R by Daniel Navarro
13. Introduction to Probability and Statistics Using R by G. Jay Kerns

• First Edition on cran r project website
• Github page for the book <- Second Edition

14. Applied Predictive Modeling by Max Kuhn and Kjell Johnson
15. The R Inferno by Patrick Burns
16. R Tips by Paul E. Johnson
17. Modern Optimization with R by Paulo Cortez
18. Advanced R by Hadley Wickham
19. OpenIntro Statistics by David M Diez, Christopher D Barr, and Mine Çetinkaya-Rundel
20. Guide to Programming and Algorithms Using R by Özgür Ergül
21. [The Art of R Programming: A Tour of Statistical Software Design]("No Link") by Norman Matloff
22. R in Action by Robert I. Kabacoff
23. Modeling and Solving Linear Programming with R by Jose M. Sallan, Oriol Lordan, Vicenc Fernandez
24. Introduction to Scientific Programming and Simulation Using R, Second Edition by Owen Jones, Robert Maillardet, Andrew Robinson
25. Data Analysis for the Life Sciences by Rafael A Irizarry and Michael I Love

• Github for the book

26. Data Mining with Rattle and R: The Art of Excavating Data for Knowledge Discovery (Use R!) by Graham Williams

Books - No Specific Software

1. Data Smart: Using Data Science to Transform Information into Insight by John W. Foreman
2. [Predictive Analytics, Revised and Updated: The Power to Predict Who Will Click, Buy, Lie, or Die]("No Link") (Revised and Upated Edition) by Eric Siegel
3. The Visual Display of Quantitative Information by Edward Tufte
4. Visualize This by Nathan Yau who
5. Data Science for Business by By Foster Provost, Tom Fawcett
6. Introduction to Probability by Joseph K. Blitzstein, Jessica Hwang

• Youtube Videos by the Author

7. The Functional Art by Alberto Cairo

From here and there

1. Top 10 Essential Books for the Data Enthusiast
2. Learn R and Python, and Have Fun Doing It
3. How to Learn Python and R, the Data Science Programming Languages, from Beginner to Intermediate and Advanced

Cheatsheets

related to R

• RStudio Cheat Sheets by RStudio
• R Reference Card by Tom Short
• R Cheat Sheet by quandl.com
• RStudio cheat sheets - ALL by RStudio

Markdown

• MARKDOWN SYNTAX - GitHub Guides by GitHub

Probability and Statistics

• Probability Cheatsheet by William Chen