R: A Survival Guide to Data Science with R

February 15, 2014 — Leave a comment

  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: (PDFR) 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 (PDFR) Miscellaneous Plots
    2. Functions (PDFR) Writing Functions in R
    3. Parallel (PDFR) 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

Source: http://onepager.togaware.com/

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