Overview

Alternative Backends for R LiveLessons teaches R programmers

techniques for dealing with large data, both in memory and in

databases.

Description

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.

About the Instructor

Jared P. Lander is the Founder and CEO of Lander

Analytics, the Organizer of the New York Open Statistical

Programming Meetup and an Adjunct Professor of Statistics at

Columbia University. With a masters from Columbia University in

statistics and a bachelors from Muhlenberg College in mathematics,

he has experience in both academic research and industry. Jared

oversees the long-term direction of the company and acts as Lead

Data Scientist, researching the best strategy, models and

algorithms for modern data needs. This is in addition to his

client-facing consulting and training. He specializes in data

management, multilevel models, machine learning, generalized linear

models, data management, visualization and statistical computing.

He is the author of 

R for Everyone, a book about R Programming geared toward

Data Scientists and Non-Statisticians alike. The book is available

from Amazon, Barnes & Noble, and InformIT. The material is

drawn from the classes he teaches at Columbia and is incorporated

into his corporate training. Very active in the data community,

Jared is a frequent speaker at conferences, universities and

meetups around the world. He is a member of the 2014 Strata New

York selection committee.

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

About LiveLessons Video Training

LiveLessons Video Training series publishes hundreds of

hands-on, expert-led video tutorials covering a wide selection of

technology topics designed to teach you the skills you need to

succeed. This professional and personal technology video series

features world-leading author instructors published by your trusted

technology brands: Addison-Wesley, Cisco Press, IBM Press, Pearson

IT Certification, Prentice Hall, Sams, and Que. Topics include: IT

Certification, Programming, Web Development, Mobile Development,

Home and Office Technologies, Business and Management, and more.

View all LiveLessons on InformIT at:

http://www.informit.com/livelessons .