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Model Comparison with Hierarchical Models

Comparing the performance of multiple machine learning models using Bayesian Hierarchical models.

Uncertainty in Neural Networks

Python
Deep Learning
Bayesian

Using MC Dropout to get probability intervals for neural network predictions.

Entity Embeddings

Python
Deep Learning

Creating entity embeddings for categorical predictors using Python.

Neural Networks in R

R
Deep Learning

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

Bayesian
R

Multi State Models

R
Bayesian

Tidy Tuesday: The Office

tidy-tuesday
R
Bayesian

Tidy Tuesday: US Tuition Data

tidy-tuesday
R

Releasing Harrier League Data

R

Tidy Tuesday: NHL Goalscorers

R
tidy-tuesday

Analysing .fit files in R

R

Forward Mode AD in R

R

Hamiltonian Monte Carlo in R

R
Bayesian

Bayesian Linear Regression with Gibbs Sampling in R

R
Bayesian

Multi-armed Bandits in Scala

Scala

Scala and Jupyter Notebook with Almond

Scala

Sampling from a distribution with a known CDF

R

Bayesian Inference using rejection sampling

R
Bayesian

A Statistical Model for Finishing Positions at the National Cross Country

R

Efficient Markov chain Monte Carlo in R with Rcpp

R
Bayesian

Harrier League Cross Country

R

MCMC with Scala Breeze

Scala
Bayesian

An Akka HTTP Client with JSON Parsing

Scala

Using Monads for Handling Failures and Exceptions

Scala

Seasonal DLM

Bayesian
Scala

The Kalman Filter in Scala

Scala
Bayesian

Practical Introduction to Akka Streaming

Scala

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