Language is a tool that allows human beings to interact and communicate with each other. The clearer we express ourselves, the better the idea is transferred from our mind to the other. The same applies to programming languages: concise, clear and consistent codes are easier to read and edit. It ...

Be honest with yourself, how many times have you wanted to restart an on-going project from scratch throwing away the current folder? Or how many times have you had to rename files and adjust folder structure to make your project simple and clear? Not to mention, all these thousands of ...

A couple of days ago I was asked to install MySQL on MacOS 10.13, and I was surprised that it was not a one-click installation, as in case of R. Unfortunately, even for me a documentation was a bit confusing, and I think it might be useful to have a guide ...

In previous post we discussed two common methods of Poisson process simulation. The reason why this trivial problem was of my interest is the fact that this is simplification of a larger scale problem of a classical ruin process. Let me remind that I focus on an extenssion of Cramé...

A couple of weeks ago a colleague of mine asked me for a help to estimate Gerber-Shiu function by Monte-Carlo methods. The function is used in ruin theory for risk processes. One can think about this function as of equialence to a moment generating function. That is if the function ...

At every turn in a non-technical post about AI for broader audience an author deems their duty to mention a deep learning as panacea for all woes. Well, it’s not. Deep learning is just one of various models, which might or might not perform better then the other techniques. ...

About a month ago RStudio published on CRAN a nice package keras. This package is an interface to a famous library keras, a high-level neural networks API written in Python for using TensorFlow, CNTK, or Theano. In this post, the focus is on TensorFlow, as default backend engine developed by ...

In pervious posts traditional regression models were fitted to real estate data. In this post tree-based models, namely random forests and gradient boosting, are trained to predict prices of the rent. These methods typically outperform traditional regression models yielding smaller errors. Furthermore, tree-based methods are much more robust to overfitting, ...

This post is dedicated to model prices of real estate by an area and a number of rooms using generalized linear model (GLM) and generalized additive model (GAM). Previous post shows how data was obtained, while in the other post the linear model is fitted to the data.