Tag: Estimation

Anintuitive idea is to assume that the density function from which the samples are drawn is smooth, and leverage it to fill-in the gaps of our high frequency histogram. This is precisely what the Kernel Density Estimation (KDE) does. It estimates the global density as the average of local density...

In the previous blog post I covered the maximum likelihood method for parameter estimation in machine learning and statistical models. In this post we’ll go over another method for parameter estimation using Bayesian inference. I’ll also show how this method can be viewed as a ...

As an engineering manager, I once led a traditional Scrum team, living the mainstream Agile culture. We spent hours defining, refining, and estimating work so that we could feed it into our fine-tuned productivity machine. We were all veterans of Agile Scrum — so why did it seem like this mach...