Jared Lander – Advanced R Programming

Jared Lander – Advanced R Programming

Check it out: Jared Lander – Advanced R Programming

In this video training Jared starts with some common data manipulation operations using various base R functions and packages like plyr, comparing the speed of in memory calculations.

He then demonstrates more advanced techniques for accomplishing the same task such as data.table, dplyr, Rcpp and parallel computation for increased speed. Finally, for when data size is an even bigger factor than speed he introduces external memory and database techniques using bibmemory, ff, SciDB, dplyr and Hadoop.

Skill Level
– Intermediate
– Advanced

What You Will Learn
– Basic Aggregation
– plyr
– dplyr
– data.table
– Rcpp
– Parallel Processing
– Code Benchmarking

Who Should Take This Course
– R programmers who already have an intermediate level of knowledge such as that gained from Reading R for Everyone.

Course Requirements
– Basic Programming Skills
– Proficiency in R, including working with packages

Table of Contents
Lesson 1: Reading XML Data
1.1. Read HTML Table
1.2. Use xpath for complex searches in HTML

1.3. xmlToList for easier parsing
Lesson 2: Faster Group Operations
2.1. Aggregate normally
2.2. tapply
2.3. ddply
2.4. data.table
2.5. dplyr
2.6. ddply parallel
2.7. foreach
2.8. dplyr with a database

Lesson 3: Rcpp for faster code
3.1. Basics of C++ with R
3.2. Writing a C++ function for R
3.3. Using C++ code in an R package

Lesson 4: Advanced Machine Learning
4.1. Recommendation Engine with RecommenderLab
4.2. Text Mining with RTextTools

Lesson 5: Network Analysis
5.1. igraph
5.2. Reading edgelists
5.3. Base plots
5.4. tkplots
5.5. rglplots
5.6. Network metrics like diameter, shortest path
5.7. Node metrics like centrality and betweenness

Lesson 6: Advanced Graphics
6.1. ggvis
6.2. rCharts