Articles by Luke Singham

How to Make a Churn Model in R

November 21, 2017 | Luke Singham

The following post details how to make a churn model in R. It was part of an interview process for which a take home assignment was one of the stages. The company stated this should take 2hrs, which is entirely unrealistic. To minimise the time cost, my analysis is very ... [Read more...]

How to Make a Churn Model in R

November 21, 2017 | Luke Singham

The following post details how to make a churn model in R. It was part of an interview process for which a take home assignment was one of the stages. The company stated this should take 2hrs, which is entirely unrealistic. To minimise the time cost, my analysis is very
[Read more...]

How to Use Shiny Containers with Shinyproxy

October 11, 2017 | Luke Singham

Aim: Setup shinyproxy as a production level way of deploying multiple containerised shiny apps with authentication. Additionally I'll demonstrate how to incorporate containerised python web apps and deploy this behind a reverse proxy using Nginx. Conceptual Overview This is a pretty significant piece of software. It renders Shiny Server Pro ... [Read more...]

Anonymous Functions in R and Python

September 13, 2017 | Luke Singham

What's in a name? That which we call a rose by any other name would smell as sweet. Normal functions Before moving to anonymous functions, let's start with what normal functions look like. In R # Define a function functionName [Read more...]

Shiny (R) Web App Performance – Profiling

August 6, 2017 | Luke Singham

Introduced at the 2016 R conference, the profvis package offers a visual way of inspecting the call stack and highlights the most memory and computationally intensive parts of your code. Run Profvis # Load library library(profvis) # Run profiler on shiny app with optional arg to save output profvis({ runApp('Projects/ [Read more...]

Benchmarking the Performance of R Code

June 17, 2017 | Luke Singham

To assess the performance of R code there's a great little package called microbenchmark. install.packages('microbenchmark') library(microbenchmark) I was particularly interested in the performance increase of a shiny application that reads in ... [Read more...]

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)