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One Page R: A Survival Guide to Data Science with R

          

A collection of useful one-page resources for a data miner, data scientist, and/or a decision scientist. The modules include code, lectures, and one-page recipes for getting things done.

Togaware Graham Williams, the founder of togaware, the developer of Rattle, free and open-source data mining software based on R, and author of Data Mining with Rattle and R: The Art of Excavating Data for Knowledge Discovery (Use R) book, has summarized useful R resources in

One Page R: A Survival Guide to Data Science with R

The include tools for the data miner, or the data scientist, and or the decision scientist.
  1. Templates for the Data Scientist
    1. A Template for Preparing Data: *OnePageR - *R
    2. A Template for Building Models: *OnePageR - *R
  2. Getting Started as a Data Scientist
    1. Getting Started with R and Rattle: *Lecture - *Laboratory
    2. Introducing and Interacting with R: *Lecture - *Laboratory
    3. BasicR - OnePage(R) - Writing R scripts
  3. Dealing With Data
    1. Read Data into R: *OnePageR - *R
    2. Explore and Summarise Data: *OnePageR - *R
    3. Transform Data: *OnePageR - *R
    4. Dealing with Dates and Time: (PDF, R) Dates and Time
    5. Visualising Data with GGPlot2: *OnePageR - *R
    6. Visualising Data with Maps *OnePageR - *R
    7. Spatial (R) Spatial Analysis
    8. Handling Big Data *OnePageR - *R
  4. Descriptive Analytics
    1. Cluster Analysis: *Lecture - *OnePageR - *R
    2. Association Analysis: *Lecture
  5. Predictive Analytics
    1. Decision Trees: *Lecture - *OnePageR - *R - *Rattle
    2. Ensembles of Decision Trees: *Lecture - *OnePageR - *R
    3. SVM (R)
    4. KernLab (R)
    5. NeuralNetworks (R)
    6. NNet (R)
  6. Model Delivery
    1. Evaluating Models: *OnePageR - *R
    2. Evaluation (R)
    3. Scoring (R)
    4. PMML (R) Exporting Models for Deployment
  7. Advanced Topics
    1. Text Mining: *OnePageR - *R
  8. Advanced R Topics
    1. Plots (PDF, R) Miscellaneous Plots
    2. Functions (PDF, R) Writing Functions in R
    3. Parallel (PDF, R) Parallel Execution
    4. Packaging (R) Pulling it Together into a Package
    5. Doing R with Style: *OnePageR - *R
    6. Literate Data Mining with KnitR: *Lecture - *OnePageR - *R

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