lopezrj · lopezrj · Sep 9, 2018 · Sep 26, 2014 · Sep 27, 2014 · Sep 27, 2014
diff --git a/.gitignore b/.gitignore
@@ -1,2 +1,4 @@
 _site
 .DS_Store
+.Rhistory
+.Rproj.user
diff --git a/README.md b/README.md
@@ -4,7 +4,7 @@ Since the beginning of the Data Science Specialization we've noticed the unbelie
 
 ## Contributing
 
-If you've created a web page, video, sideshow, or any other kind of media you think should be shared through this directory you should:
+If you've created a web page, video, slideshow, or any other kind of media you think should be shared through this directory you should:
 
 1. Fork this repository.
 2. Add a link to your content on the appropriate course page.

diff --git a/about.md b/about.md
@@ -19,6 +19,10 @@ The [Data Science Specialization](https://www.coursera.org/specialization/jhudat
 - [Kevin Markham](http://www.dataschool.io/)
 - Derek Franks
 - David Hood
+- [Leonard Greski](https://github.com/lgreski)
 - Michael Sachs
 - Allan Inocêncio de Souza Costa
-- [stepds](https://github.com/stepds)
+- [stepds](https://github.com/stepds)
+- Bastiaan Quast
+- [Xing Su](http://sux13.github.io/DataScienceSpCourseNotes/)
+- [Edmund julian Ofilada](https://github.com/DocOfi)
diff --git a/capstone.md b/capstone.md
@@ -0,0 +1,14 @@
+---
+title: "Capstone"
+permalink: /capstone/
+layout: page
+---
+## Reference Material
+
+- [Speech and Language Processing, 3rd Edition](https://web.stanford.edu/~jurafsky/slp3/) Working version of Jurafsky, et. al. book on natural language processing whose content on n-grams is helpful for the capstone.
+
+## Course Project
+
+- [n-gram Computations and Computer Capacity](http://bit.ly/2couvxh) Explains the amount of memory required to convert the text files for the course project into n-grams, using the <strong>quanteda</strong> package.
+- [Capstone Strategy](http://bit.ly/2rGcgc6) Describes a general strategy to get through the Capstone: use the simplest approaches possible.
+- [Choosing a Text Analysis Package](http://bit.ly/2qagsPa) Reviews pros and cons of various R packages used for natural language processing, in the context of requirements for the Capstone project. 
diff --git a/curated.md b/curated.md
@@ -1,6 +1,85 @@
 ---
 layout: page
-title: Curated Knowledge
+title: Curated Pages
 permalink: /curated/
 ---
 
+### Analytics
+
+- [Huge Trello Board Collection of Data Science Resources](https://trello.com/b/rbpEfMld/data-science)
+- [Diving Into Data Science Flipboard](https://flipboard.com/@thiakx/diving-into-data-science-5823ectuy)
+- [OLAP Operation in R](http://architects.dzone.com/articles/olap-operation-r)
+- [Journal of Statistical Software: Tidy data](http://www.jstatsoft.org/v59/i10/paper)
+- [Verzani: simpleR – Using R for Introductory Statistics](http://cran.r-project.org/doc/contrib/Verzani-SimpleR.pdf)
+- [Data Visualization packages](http://www.datavis.ca/R/)
+- [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/)
+- [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/)
+- [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)
+- [Data from 538](https://github.com/fivethirtyeight/data)
+
+### Command Line
+
+- [explainshell.com - match command-line arguments to their help text](http://explainshell.com/)
+- [The Command Line Crash Course - Quick course in using the command line](http://cli.learncodethehardway.org/book/)
+- [Mastering the command line, in one page](https://github.com/jlevy/the-art-of-command-line/blob/master/README.md)
+
+### R
+
+- [Try R](http://tryr.codeschool.com/)
+- [The R Book by Michael J. Crawley](https://archive.org/details/TheRBook/)
+- [Univ. of Calif. Riverside R Programming](http://manuals.bioinformatics.ucr.edu/home/programming-in-r#TOC-R-Basics)
+- [G. Sanchez - Strings in R](http://gastonsanchez.com/Handling_and_Processing_Strings_in_R.pdf)
+- [The Lubridate Package](http://www.jstatsoft.org/v40/i03/paper)
+- [Google Developers R Programming Video Lectures](http://www.r-bloggers.com/google-developers-r-programming-video-lectures/)
+- [awesome R](https://github.com/qinwf/awesome-R) - A curated list of awesome R frameworks, packages and software. 
+- [awesome machine learning](https://github.com/josephmisiti/awesome-machine-learning#r) - A curated list of awesome Machine Learning frameworks, libraries and software. 
+- [Google's R Style Guide](https://google-styleguide.googlecode.com/svn/trunk/Rguide.xml)
+- [Tufte-style HTML in rmarkdown](http://sachsmc.github.io/tufterhandout/)
+- [Creating an R Package](http://hilaryparker.com/2014/04/29/writing-an-r-package-from-scratch/)
+- [R Packages (Hadley online book)](http://r-pkgs.had.co.nz/) - How to write your own R packages.
+- [Beautiful ggplot2 Cheatsheet](http://zevross.com/blog/2014/08/04/beautiful-plotting-in-r-a-ggplot2-cheatsheet-3/)
+- [Intro to Graphics](http://bcb.dfci.harvard.edu/~aedin/courses/Bioconductor/2.Plotting.pdf)
+- [data.table cheat sheet](https://s3.amazonaws.com/assets.datacamp.com/img/blog/data+table+cheat+sheet.pdf)
+- [Exploratory Data Analysis with data.table](http://varianceexplained.org/RData/lessons/lesson4/)
+- [Fast summary statistics in R with data.table](http://blog.yhathq.com/posts/fast-summary-statistics-with-data-dot-table.html)
+- [R online in r-fiddle.org](http://www.r-fiddle.org/)
+
+### Probability and Statistics
+
+- [Probability and Statistics Cookbook](http://matthias.vallentin.net/probability-and-statistics-cookbook/)
+
+### GitHub
+
+- [Official Git Tutorial](http://git-scm.com/docs/gittutorial)
+- [Git - Simple Guide](http://rogerdudler.github.io/git-guide/)
+- [Git Immersion - A guided tour through the fundamentals of Git](http://gitimmersion.com/)
+- [GitHub - Dealing with Multiple Accounts](http://hmkcode.com/git-tutorial/how-to-deal-with-multiple-github-accounts-on-one-computer/)
+- [Try Git](https://try.github.io/levels/1/challenges/1)
+- [Learn Git Branching: Interactive Game](http://pcottle.github.com/learnGitBranching/)
+- [Atlassian Git Tutorials - Branches](https://www.atlassian.com/git/tutorials/using-branches/)
+
+### Reproducible Research
+- [Markdown live demo](http://markdown-here.com/livedemo.html)
+- [Boosting Slides by Ron Meir](https://github.com/Aratinga/Misc/blob/master/BoostingTutorial.pdf) 
+- [Reproducible Research website](http://reproducibleresearch.net/)
+
+### Machine Learning
+- [UC Irvine Machine Learning Data Repository](http://archive.ics.uci.edu/ml/)
+
+### Textbooks
+- [OpenIntro textbook](https://www.openintro.org/stat/textbook.php)
+- [Statlect - The digital textbook on probability and statistics](http://www.statlect.com/)
+- [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)
+- [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)
+
+### Further Reading
+
+- [Data Elixir - Free weekly newsletter of the best data-related resources and inspirations from around the web.](http://dataelixir.com/?referred=true)
+- [Linkedin - Top 10 Big Data and Analytics References](https://www.linkedin.com/pulse/article/20140810194033-111366377-top-10-big-data-and-analytics-references)
+- [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)
+- [Data Science Central : a great repository of news and resources for data science practitioners.](http://www.datasciencecentral.com)
+- [Data Science Ontology - A visualized overview of Data Science concepts and tools](http://datascienceontology.com/)
+
+### Data Science Groups, Meetups, and Networking
+
+- [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)
diff --git a/ddp.md b/ddp.md
@@ -5,3 +5,21 @@ permalink: /ddp/
 ---
 
 - [Slidify to Github walkthrough](http://rpubs.com/thoughtfulbloke/25103)
+- [ggvis and rmarkdown slides with interactive plots](http://qua.st/ggvis-shiny-html5-slides)
+
+## Shiny
+- Choropleth of PBS WARN Distribution of Wireless Emergency Alerts
+  - [Code for Shiny App](https://github.com/amsilvr/shiny_choropleth)
+  - [App running on shinyapps.ip](https://silverman.shinyapps.io/warn_wea/)
+- [Shiny app to simulate 401K growth with interactive plots](http://www.mephistosoftware.com/shiny/401k_simulator/)
+- [Shiny Video Tutorials Playlist on Youtube](http://www.youtube.com/playlist?list=PL6wLL_RojB5xNOhe2OTSd-DPkMLVY9DfB)
+- [Tutorial on writing Shiny simulation apps](https://github.com/homerhanumat/shinyTutorials)
+- [Dockerize a Shiny App](http://www.rmining.net/2015/04/30/dockerizing-a-shiny-app/)
+- [Git pushing Shiny Apps with Docker/Dokku](http://www.rmining.net/2015/05/11/git-pushing-shiny-apps-with-docker-dokku/)
+- [Share your Shiny Apps with Docker and Kitematic](http://www.rmining.net/2015/08/10/share-your-shiny-apps-with-docker-and-kitematic/)
+- [Shinyapps.io: Configuring Application Timeout](https://github.com/lgreski/datasciencectacontent/blob/master/markdown/dataProd-shinyTimeoutConfig.md)
+- [Plotting Natural Disasters](http://www.rpubs.com/DocOfi/367052)
+
+## Comprehensive Notes
+
+- Complete notes for [Developing Data Products](http://sux13.github.io/DataScienceSpCourseNotes/)
diff --git a/eda.md b/eda.md
@@ -4,3 +4,13 @@ title: Exploratory Data Analysis
 permalink: /eda/
 ---
 
+- [Creating a Kite Graph](http://rpubs.com/thoughtfulbloke/kitegraph)
+- [Analyzing Top/Green500 Supercomputer Technology Trends](http://github.com/ww44ss/Exascalar-Analysis-)
+- [Emissions Choropleth Maps](https://github.com/BillSeliger/ExData_Plotting2)
+- [Data Analysis using Twitter API and Python](http://blog.impiyush.com/2015/03/data-analysis-using-twitter-api-and.html)
+- [Exploratory Data Analysis using Flexdashboard](http://rpubs.com/DocOfi/350830)
+- [Plotting using Metricsgraphics](http://www.rpubs.com/DocOfi/352947)
+
+## Comprehensive Notes
+
+- Complete notes for [Exploratory Data Analysis](http://sux13.github.io/DataScienceSpCourseNotes/)
diff --git a/getclean.md b/getclean.md
@@ -6,3 +6,22 @@ permalink: /getclean/
 
 - [Subsetting example walkthrough](http://rpubs.com/thoughtfulbloke/subset)
 - [Apples to Oranges Data Organisation Challenge](https://github.com/thoughtfulbloke/faoexample)
+- [dplyr introductory tutorial](https://www.youtube.com/watch?v=jWjqLW-u3hc) and [R Markdown document](http://rpubs.com/justmarkham/dplyr-tutorial): A 39-minute video tutorial that covers the five basic dplyr "verbs" and a dozen other dplyr functions. dplyr is an [update](http://blog.rstudio.org/2014/01/17/introducing-dplyr/) to the plyr package, useful for subsetting, sorting, summarizing, and merging data using a more intuitive syntax than plyr or base R.
+- [dplyr "going deeper" tutorial](https://www.youtube.com/watch?v=2mh1PqfsXVI) and [R Markdown document](http://rpubs.com/justmarkham/dplyr-tutorial-part-2): A 37-minute video tutorial that covers the new functionality in dplyr versions 0.3 and 0.4.
+- [Downloading files general advice](http://rpubs.com/thoughtfulbloke/downloadtips)
+- [Codebook sample](https://gist.github.com/kirstenfrank/218c36a1938055d0f4e4)
+- [Second Codebook sample](https://gist.github.com/kirstenfrank/699abe3e16fd1dc36e5d)
+- [Query string (and other fields-within-fields) unrolling](http://rpubs.com/schnee/32988)
+- [Pre-processing Excel files before loading them into R](https://github.com/alkashef/cleaningexceldata)
+- [Codebook template that can be used in the Getting and Cleaning Data project](https://gist.github.com/JorisSchut/dbc1fc0402f28cad9b41)
+- ["Real world" example - reading American Community Survey 2000 PUMS Data:](https://github.com/lgreski/acsexample) Demonstrates how to extract records of a given type from a data file containing multiple record types, and how to use an Excel-based code book to specify arguments for reading a fixed-width file.
+- [18 Months of CTA advice](https://thoughtfulbloke.wordpress.com/2015/08/31/hello-world)
+- [Common Problems: Quiz 1 - Missing Java Runtime](http://bit.ly/2jjtyXM) Explains how to solve the problem of a missing Java Runtime for the question that requires students to process a Microsoft Excel spreadsheet. 
+- [Strategy for Reading Files & APIs / Quiz 2](http://bit.ly/2e4L5oF)
+- [Common Problems: Quiz 2 - sqldf() driver fails to connect](http://bit.ly/2kD2KTY)
+- [Tutorial: Downloading Files](http://bit.ly/2iP2suj) Illustrates various ways of downloading files, including binary and text files. 
+- [Creating dataframes from xml data](https://www.dropbox.com/s/7bbzzp4bwsmfl5y/CreatingDataframesfrom%20XmlFiles.odt?dl=0)
+
+## Comprehensive Notes
+
+- Complete notes for [Getting and Cleaning Data](http://sux13.github.io/DataScienceSpCourseNotes/)
diff --git a/index.md b/index.md
@@ -4,7 +4,7 @@ layout: page
 
 ## Table of Contents
 
-This is site is meant to serve as a directory for the amazing content the
+This site is meant to serve as a directory for the amazing content the
 community has created around the Data Science Specialization. If you are
 interested in contributing [click here](https://github.com/DataScienceSpecialization/DataScienceSpecialization.github.io#contributing).
 
@@ -17,6 +17,7 @@ interested in contributing [click here](https://github.com/DataScienceSpecializa
 7. [Regression Models](/regmod/)
 8. [Practical Machine Learning](/pml/)
 9. [Developing Data Products](/ddp/)
+10. [Capstone](/capstone/)
 
 - [Other Resources](/other/)
-- [Curated Knowledge](/curated/)
+- [Curated Pages](/curated/)
diff --git a/other.md b/other.md
@@ -4,7 +4,30 @@ title: Other Resources
 permalink: /other/
 ---
 
-## Troubleshooting
+## Configuring R and RStudio (Linux)
 
 - [Installing xlsx and XML packages on Debian Wheezy](http://allanino.me/blog/programming/installing-some-r-packages/)
+- [Rscript to customize R environment](http://bit.ly/r-customize-script) - Installs packages used in the specialization.
+- [Installing Some Basic R Packages in Ubuntu; Ibrahim El Merehbi](http://elmerehbi.wordpress.com/2014/09/09/installing-some-basic-r-packages-in-ubuntu)
+- [Using Projects in RStudio](https://support.rstudio.com/hc/en-us/articles/200526207-Using-Projects)
+- [Using Version Control with RStudio](https://support.rstudio.com/hc/en-us/articles/200532077-Version-Control-with-Git-and-SVN)
+- [Using R behind HTTP/HTTPS Proxy](https://support.rstudio.com/hc/en-us/articles/200488488-Configuring-R-to-Use-an-HTTP-or-HTTPS-Proxy)
+
+### Ignoring R & RStudio files
+- [gitignore template for R](https://github.com/github/gitignore/blob/master/R.gitignore) (source:[gitignore](https://github.com/github/gitignore))
+- [Github Help - Using Git / Ignoring files](https://help.github.com/articles/ignoring-files/)
+
+## Troubleshooting
 - [Windows batch file to work around RStudio startup issues](https://github.com/stepds/contrib-DataScienceSpecialization/blob/master/README.md)
+
+## Pre-built virtual machines for R development.
+- [Here's a pre-built lightweight Linux machine with R and RStudio already installed](https://github.com/queirozfcom/r-box). You just need to install [vagrant](https://www.vagrantup.com/downloads.html), download (or clone) the github repository and you'll get a clean ubuntu machine with the tools you'll need for the assignments. 
+
+- [Data Science Toolbox](http://datasciencetoolbox.org/) - A virtual environment that allows you to start doing data science in a matter of minutes.
+
+- [Virtual machine with RStudio server and github setup](https://github.com/tboloo/vagrant-rstudio) - A VirtualBox, Vagrant & chef-solo managed virtual machine which provides RStudio server with git & github setup
+
+## Deploying and sharing Shiny Apps with Docker
+- [Dockerize a Shiny App](http://www.rmining.net/2015/04/30/dockerizing-a-shiny-app/)
+- [Git pushing Shiny Apps with Docker/Dokku](http://www.rmining.net/2015/05/11/git-pushing-shiny-apps-with-docker-dokku/)
+- [Share your Shiny Apps with Docker and Kitematic](http://www.rmining.net/2015/08/10/share-your-shiny-apps-with-docker-and-kitematic/)
diff --git a/pml.md b/pml.md
@@ -7,3 +7,31 @@ permalink: /pml/
 ## Model Evaluation
 
 - [Simple Guide to Confusion Matrix Terminology (sensitivity, specificity, etc.)](http://www.dataschool.io/simple-guide-to-confusion-matrix-terminology/)
+- ROC curves and Area Under the Curve explained: [video tutorial](http://youtu.be/OAl6eAyP-yo), [companion blog post](http://www.dataschool.io/roc-curves-and-auc-explained/) (with video transcript and screenshots)
+
+## Supplementary Videos
+
+- [What is machine learning, and how does it work?](https://www.youtube.com/watch?v=elojMnjn4kk): A high-level overview of machine learning in a 10-minute video
+- [Video lectures from "An Introduction to Statistical Learning"](http://www.dataschool.io/15-hours-of-expert-machine-learning-videos/): Videos for Chapters 4, 5, 6, 8, and 10 can help to deepen your understanding of the topics presented in this course.
+
+## Machine Learning Competitions
+
+- [Participating in Kaggle's Allstate Purchase Prediction Challenge](http://www.dataschool.io/kaggle-allstate-purchase-prediction-challenge/): Description of what it's like to compete in a Kaggle competition, including links to a project paper, R code, presentation slides, and a presentation video.
+
+## Choosing a Machine Learning Model
+
+- [Comparing Supervised Learning Algorithms](http://www.dataschool.io/comparing-supervised-learning-algorithms/): Comparing 8 common supervised learning algorithms (for regression and classification) on 13 different dimensions.
+
+## Content Related to the Lectures
+
+- Complete notes for [Practical Machine Learning](http://sux13.github.io/DataScienceSpCourseNotes/)
+- [Week 4: Combining Predictors -- Math Explained](https://github.com/lgreski/datasciencectacontent/blob/master/markdown/pml-combiningPredictorsBinomial.md)
+
+## Configuring Github Pages with RStudio for PML Project 
+
+- Step by step instructions to [Configure Github Pages with RStudio](https://github.com/lgreski/datasciencectacontent/blob/master/markdown/pml-ghPagesSetup.md) to support the PML course project. 
+
+## Improving Runtime Performance of Caret 
+
+- Step by step instructions to [implement parallel processing in caret::train()](https://github.com/lgreski/datasciencectacontent/blob/master/markdown/pml-randomForestPerformance.md) on a random forest model, along with runtime performance analysis for a variety of laptops, ranging from an Intel Atom-based tablet to a quad-core i7 processor. 
+
diff --git a/regmod.md b/regmod.md
@@ -4,3 +4,10 @@ title: Regression Models
 permalink: /regmod/
 ---
 
+## Supplementary Videos
+
+- [Video lectures from "An Introduction to Statistical Learning"](http://www.dataschool.io/15-hours-of-expert-machine-learning-videos/): Videos for Chapter 3 can help to deepen your understanding of regression.
+
+## Comprehensive Notes
+
+- Complete notes for [Regression Models](http://sux13.github.io/DataScienceSpCourseNotes/)
diff --git a/repres.md b/repres.md
@@ -6,4 +6,11 @@ permalink: /repres/
 
 - [Turning a RPubs document into a Github website walkthrough](https://github.com/thoughtfulbloke/appleorange)
 - [Introduction to knitr with rmarkdown](https://sachsmc.github.io/knit-git-markr-guide/knitr/knit.html)
+- [Trends and severity of Data Breaches](http://rpubs.com/ww44ss/29389)
+- [Benefit-cost analysis of a park user fee](https://rstudio-pubs-static.s3.amazonaws.com/72135_dc45211d976842c2a9a8c8b5f2472ff0.html)
+- [Data Lake Integrity](http://rpubs.com/rshane/81297)
+- [ProjectTemplate in RStudio with Git](http://padamson.github.io/r/rstudio/projecttemplate/git/2016/01/17/projecttemplate-in-rstudio-with-git.html)
 
+## Comprehensive Notes
+
+- Complete notes for [Reproducible Research](http://sux13.github.io/DataScienceSpCourseNotes/)