Python-bloggers

Markov Chain Monte Carlo (MCMC) methods can be used to estimate the parameters of linear regression models. In this post, the distributional forms and algorithms associated with two Gibbs sampling approaches are outlined: the full conditionals a...

I always had trouble spelling Dijkstra correctly until someone pointed out “It’s just D, followed by i-j-k, then stra”. Once it was pointed out that i-j-k is represented sequentially in alphabetical order, spelling Dijkstra becomes trival - almo...

Convolutional Neural networks (CNNs) have been found to be very effective at tasks such as facial recognition, video analysis, anomaly detections and semantic parsing. An image can be considered a graph with a very regular structure (i.e., pixel...

Markov Chain Monte Carlo (MCMC) methods can be used to estimate the parameters of linear regression models. In this post, the distributional forms and algorithms associated with two Gibbs sampling approaches are outlined: the full conditionals ap...

Convolutional Neural networks (CNNs) have been found to be very effective at tasks such as facial recognition, video analysis, anomaly detections and semantic parsing. An image can be considered a graph with a very regular structure (i.e., pixels...

I always had trouble spelling Dijkstra correctly until someone pointed out “It’s just D, followed by i-j-k, then stra”. Once it was pointed out that i-j-k is represented sequentially in alphabetical order, spelling Dijkstra becomes trival - almos...

Hyperparameter tuning with GPopt, based on Gaussian processes

In this post, we use Python to improve a simple GLM by insights from a boosted trees model.

Bessel’s correction is the use of instead of in the sample variance formula where is the number of observations in a sample. This method corrects the bias in the estimation of the population variance. Recall that bias is defined as: where r...

An analysis may require the ability to generate correlated random samples. For example, imagine we have monthly returns for three financial indicators over a 20 year period. We are interested in modeling these returns using parametric distributi...