Simulating data with Bayesian networks
Bayesian networks are really useful for many applications and one of those is to simulate new data. Bayes nets represent […]
Category: Data Science
Use more of your data with matrix factorisation
Previously I posted on how to apply gradient descent on linear regression as an example. With that as background it’s […]
Bayesian estimation of fatality rates and accidents involving cyclists on Queensland roads
In my previous post I built a Shiny app mapping accidents on Queensland roads which was great at showing the […]
Queensland road accidents mapped with Shiny and leaflet in R
The Queensland government collects data on road accidents dating back to 1st January 2001 and details characteristics of the incident […]
Applying gradient descent – primer / refresher
Every so often a problem arises where it’s appropriate to use gradient descent, and it’s fun (and / or easier) […]
Martingale strategies don’t work, but we knew that – Simulation analysis in R
It’s generally accepted that Martingale betting strategies don’t work. But people still gravitate towards them because they are intuitive. I […]
Adding Custom Fonts to ggplot in R
ggplot – You can spot one from a mile away, which is great! And when you do it’s a silent […]
The Most Amount of Rain over a 10 Day Period on Record
Townsville, Qld, has been inundated with torrential rain and has broken the record of the largest rainfall over a 10 […]
Synthesising Multiple Linked Data Sets and Sequences in R
In my last post I looked at generating synthetic data sets with the ‘synthpop’ package, some of the challenges and […]
Generating Synthetic Data Sets with ‘synthpop’ in R
Synthpop – A great music genre and an aptly named R package for synthesising population data. I recently came across […]
Q-learning example with Liar’s Dice in R
In my last post I coded Liar’s Dice in R and some brainless bots to play against. I build on […]
Liar’s Dice in R
I have been playing Red Dead Redemption 2, immersing myself in the Old West as I did with the first […]
Hidden Markov Model example in R with the depmixS4 package
Recently I developed a solution using a Hidden Markov Model and was quickly asked to explain myself. What are they […]
Bayesian Network Example with the bnlearn Package
Bayesian Networks are probabilistic graphical models and they have some neat features which make them very useful for many problems. […]
Simple Parallel Processing in R
I recently purchased a new laptop with an Intel i7-8750 6 core CPU with multi-threading meaning I have 12 logical […]
