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1 | 1 | ---
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2 | 2 | layout: page
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3 |
| -title: Curated Knowledge |
| 3 | +title: Curated Pages |
4 | 4 | permalink: /curated/
|
5 | 5 | ---
|
6 | 6 |
|
| 7 | +### Analytics |
| 8 | + |
| 9 | +- [Huge Trello Board Collection of Data Science Resources](https://trello.com/b/rbpEfMld/data-science) |
| 10 | +- [Diving Into Data Science Flipboard](https://flipboard.com/@thiakx/diving-into-data-science-5823ectuy) |
| 11 | +- [OLAP Operation in R](http://architects.dzone.com/articles/olap-operation-r) |
| 12 | +- [Journal of Statistical Software: Tidy data](http://www.jstatsoft.org/v59/i10/paper) |
| 13 | +- [Verzani: simpleR – Using R for Introductory Statistics](http://cran.r-project.org/doc/contrib/Verzani-SimpleR.pdf) |
| 14 | +- [Data Visualization packages](http://www.datavis.ca/R/) |
| 15 | +- [Visualization hints: plotting numeric data by groups](http://www.r-bloggers.com/visualization-series-insight-from-cleveland-and-tufte-on-plotting-numeric-data-by-groups/) |
| 16 | +- [Matrix rotation for image and contour plots in R](http://blog.snap.uaf.edu/2012/06/08/matrix-rotation-for-image-and-contour-plots-in-r/) |
| 17 | +- [Fig Data: 11 Tips on How to Handle Big Data in R (and 1 Bad Pun)](http://theodi.org/blog/fig-data-11-tips-how-handle-big-data-r-and-1-bad-pun) |
| 18 | +- [Data from 538](https://github.com/fivethirtyeight/data) |
| 19 | + |
| 20 | +### Command Line |
| 21 | + |
| 22 | +- [explainshell.com - match command-line arguments to their help text](http://explainshell.com/) |
| 23 | +- [The Command Line Crash Course - Quick course in using the command line](http://cli.learncodethehardway.org/book/) |
| 24 | +- [Mastering the command line, in one page](https://github.com/jlevy/the-art-of-command-line/blob/master/README.md) |
| 25 | + |
| 26 | +### R |
| 27 | + |
| 28 | +- [Try R](http://tryr.codeschool.com/) |
| 29 | +- [The R Book by Michael J. Crawley](https://archive.org/details/TheRBook/) |
| 30 | +- [Univ. of Calif. Riverside R Programming](http://manuals.bioinformatics.ucr.edu/home/programming-in-r#TOC-R-Basics) |
| 31 | +- [G. Sanchez - Strings in R](http://gastonsanchez.com/Handling_and_Processing_Strings_in_R.pdf) |
| 32 | +- [The Lubridate Package](http://www.jstatsoft.org/v40/i03/paper) |
| 33 | +- [Google Developers R Programming Video Lectures](http://www.r-bloggers.com/google-developers-r-programming-video-lectures/) |
| 34 | +- [awesome R](https://github.com/qinwf/awesome-R) - A curated list of awesome R frameworks, packages and software. |
| 35 | +- [awesome machine learning](https://github.com/josephmisiti/awesome-machine-learning#r) - A curated list of awesome Machine Learning frameworks, libraries and software. |
| 36 | +- [Google's R Style Guide](https://google-styleguide.googlecode.com/svn/trunk/Rguide.xml) |
| 37 | +- [Tufte-style HTML in rmarkdown](http://sachsmc.github.io/tufterhandout/) |
| 38 | +- [Creating an R Package](http://hilaryparker.com/2014/04/29/writing-an-r-package-from-scratch/) |
| 39 | +- [R Packages (Hadley online book)](http://r-pkgs.had.co.nz/) - How to write your own R packages. |
| 40 | +- [Beautiful ggplot2 Cheatsheet](http://zevross.com/blog/2014/08/04/beautiful-plotting-in-r-a-ggplot2-cheatsheet-3/) |
| 41 | +- [Intro to Graphics](http://bcb.dfci.harvard.edu/~aedin/courses/Bioconductor/2.Plotting.pdf) |
| 42 | +- [data.table cheat sheet](https://s3.amazonaws.com/assets.datacamp.com/img/blog/data+table+cheat+sheet.pdf) |
| 43 | +- [Exploratory Data Analysis with data.table](http://varianceexplained.org/RData/lessons/lesson4/) |
| 44 | +- [Fast summary statistics in R with data.table](http://blog.yhathq.com/posts/fast-summary-statistics-with-data-dot-table.html) |
| 45 | +- [R online in r-fiddle.org](http://www.r-fiddle.org/) |
| 46 | + |
| 47 | +### Probability and Statistics |
| 48 | + |
| 49 | +- [Probability and Statistics Cookbook](http://matthias.vallentin.net/probability-and-statistics-cookbook/) |
| 50 | + |
| 51 | +### GitHub |
| 52 | + |
| 53 | +- [Official Git Tutorial](http://git-scm.com/docs/gittutorial) |
| 54 | +- [Git - Simple Guide](http://rogerdudler.github.io/git-guide/) |
| 55 | +- [Git Immersion - A guided tour through the fundamentals of Git](http://gitimmersion.com/) |
| 56 | +- [GitHub - Dealing with Multiple Accounts](http://hmkcode.com/git-tutorial/how-to-deal-with-multiple-github-accounts-on-one-computer/) |
| 57 | +- [Try Git](https://try.github.io/levels/1/challenges/1) |
| 58 | +- [Learn Git Branching: Interactive Game](http://pcottle.github.com/learnGitBranching/) |
| 59 | +- [Atlassian Git Tutorials - Branches](https://www.atlassian.com/git/tutorials/using-branches/) |
| 60 | + |
| 61 | +### Reproducible Research |
| 62 | +- [Markdown live demo](http://markdown-here.com/livedemo.html) |
| 63 | +- [Boosting Slides by Ron Meir](https://github.com/Aratinga/Misc/blob/master/BoostingTutorial.pdf) |
| 64 | +- [Reproducible Research website](http://reproducibleresearch.net/) |
| 65 | + |
| 66 | +### Machine Learning |
| 67 | +- [UC Irvine Machine Learning Data Repository](http://archive.ics.uci.edu/ml/) |
| 68 | + |
| 69 | +### Textbooks |
| 70 | +- [OpenIntro textbook](https://www.openintro.org/stat/textbook.php) |
| 71 | +- [Statlect - The digital textbook on probability and statistics](http://www.statlect.com/) |
| 72 | +- [An Introduction to Statistical Learning with Applications in R](http://www-bcf.usc.edu/~gareth/ISL/) [[PDF, 4th printing]](http://www-bcf.usc.edu/~gareth/ISL/ISLR%20Fourth%20Printing.pdf) |
| 73 | +- [The Elements of Statistical Learning: Data Mining, Inference, and Prediction](http://statweb.stanford.edu/~tibs/ElemStatLearn/) [[PDF, 10th ed]](http://statweb.stanford.edu/~tibs/ElemStatLearn/printings/ESLII_print10.pdf) |
| 74 | + |
| 75 | +### Further Reading |
| 76 | + |
| 77 | +- [Data Elixir - Free weekly newsletter of the best data-related resources and inspirations from around the web.](http://dataelixir.com/?referred=true) |
| 78 | +- [Linkedin - Top 10 Big Data and Analytics References](https://www.linkedin.com/pulse/article/20140810194033-111366377-top-10-big-data-and-analytics-references) |
| 79 | +- [Linkedin - Let's Get Nerdy: Data Analytics for Business Leaders Explained](https://www.linkedin.com/pulse/article/20140918162814-111366377-let-s-get-nerdy-data-analytics-for-business-leaders-explained) |
| 80 | +- [Data Science Central : a great repository of news and resources for data science practitioners.](http://www.datasciencecentral.com) |
| 81 | +- [Data Science Ontology - A visualized overview of Data Science concepts and tools](http://datascienceontology.com/) |
| 82 | + |
| 83 | +### Data Science Groups, Meetups, and Networking |
| 84 | + |
| 85 | +- [LinkedIn Data Science Specialisation Group](https://www.linkedin.com/groups/Coursera-Specialization-Data-Science-7495000?home=&gid=7495000&trk=anet_ug_hm&goback=%2Egmp_7495000) |
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