A science blog about my spare time data analysis projects.
Efficient data processing lies at the heart of modern machine learning. Kernel smoothing, a versatile non-parametric technique, benefits significantly from performance improvements through optimized algorithms and frameworks. In this post, …
Introduction In GLMs, we often encounter scenarios where we need to account for exposure or adjust for certain factors. Both offset and weights play crucial roles in achieving this. Let’s …
Problem Statement Let thus , we construct a stochastic process as , this kind of random variable are called hypoexponential random variables. We define a counting process such that . …
Introduction A while ago I applied NLP strategies to implement an algorithm that is capable to guess a password. Since then a new method called transformer was developed and successfully …
I recently realized that I have a certain habit when it comes to stock trading even though I used to tell myself that “every trading strategy is useless because the …
Working at my post about the dask cluster, I realized that the code snippets presented in the post will eventually change in my GitHub Repo. I wanted to avoid having …
This post is supposed to give a brief introduction in Frequency-Severity models. These models are very popular for determine the optimal price for an insurance. We will take a look …
In the last two articles we covered the topics “How to teach a computer gamerules” and “The Multiarmed Bandit Problem”. Indeed these two articles where intended to be an introduction …
1. Formulation of the Multiarmed Bandit Problem Consider the following problem: A gambler enters a casino with slot machines. The probability to receive a reward for each slot machine follows …
To explain the registration problem i will start with an example. In Figure 1 the pinch force dataset is shown, to collect the data a group of 20 subjects were …