Blog
Neural Networks in R
This post explores how to create a simple neural network to learn a linear function and a non-linear function using both standard R and the Torch library for R.
Functional Programming and Hidden Markov Models
Multi State Models
Tidy Tuesday: The Office
Tidy Tuesday: US Tuition Data
Releasing Harrier League Data
Tidy Tuesday: NHL Goalscorers
Analysing .fit files in R
Forward Mode AD in R
Hamiltonian Monte Carlo in R
Bayesian Linear Regression with Gibbs Sampling in R
Multi-armed Bandits in Scala
Scala and Jupyter Notebook with Almond
Sampling from a distribution with a known CDF
Bayesian Inference using rejection sampling
A Statistical Model for Finishing Positions at the National Cross Country
Efficient Markov chain Monte Carlo in R with Rcpp
Harrier League Cross Country
MCMC with Scala Breeze
An Akka HTTP Client with JSON Parsing
Using Monads for Handling Failures and Exceptions
Seasonal DLM
