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A Survival Guide to Data Science with R

These draft chapters weave together a collection of tools for the data scientist—tools that are all part of the R Statistical Software Suite.

Each chapter is a collection of one (or more) pages that cover particular aspects of the topic. The chapters can be worked through as a hands-on guide to a specific task and then used as a reference guide. Each page aims to be a bite sized chunk for hands-on learning, building on what has gone before. Many chapters also have a lecture pack and a laboratory session where a number of tasks can be completed. The R code sitting behind each chapter is also provided and can be easily run standalone to replicate the material presented in the chapter.

The material begins with an overview of how an organisation should go about setting up their Analytics capability and then introduce the Data Scientist to R.

Part 1: Data Science

Data Mining, Analytics, and Data Science Rattle to R

An Introduction to R Programming Literate Data Science with KnitR

More Basics of R



Part 2: Dealing With Data

A Template for Preparing Data

Reading Data into R

Open Access Data via the CKAN API

Exploring and Summarising Data

Visualising Data with GGPlot2

Transforming Data

Case Study: Analysis of Sea Ports

Case Study: Web Log Analysis

Part 3: Building Models

A Template for Building Models

Cluster Analysis

Association Analysis Decision Trees

Ensembles of Decision Trees

Support Vector Machines Neural Networks Naive Bayes

Multivariate Adaptive Regression Splines

Evaluating Models

Scoring (R) PMML (R) Exporting Models for Deployment

Part 4: Advanced R and Analytics

Strings

Dates and Time

Spatial Data

Big Data

Exploring Different Plots

Writing Functions

Parallel Processing

Environments

Text Mining

Social Network Analysis Genetic Programming Time Series Analysis



Part 5: Appendicies

Doing R with Style

Packaging (R) Pulling it Together into a Package



To check out all this information, click here. For other articles about R, click here.

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