Guessing Passwords using an LSTM Network
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 …
A science blog about my spare time data analysis projects.
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 …
In this article we will show a way to do high performance parallel computing at a Kubernetes cluster using task. A primary focus is that we want to archive the …
1. Setup In a previous post it was shown how to speed up the computation of a kernel density using the Fast Fourier Transform. Conceptually a kernel density is not …
1. Setup This Post is about how to speed up the computation kernel density estimators using the FFT (Fast Fourier Transform). Let be be a random sample drawn from an …
In a previous post I covered how to apply classical linear estimators like support vector machines or logistic regression to a non-linear dataset using the kernel method. This article can …
1. Introduction This blog post is about Support Vector Machines (SVM), but not only about SVMs. SVMs belong to the class of classification algorithms and are used to separate one …
1. Kernel Regression using Pyspark In a previous article I presented an implementation of a kernel denisty estimation using pyspark. It is thus not difficult to modify the algorithm to …
1. A Nonparametric Density implementation in Spark One of my previous blog post concerns about nonparametric density estimation. In this post i presented some Matlab code. An advantage of this …
1. Functional Regression Let the covariate be an at least twice continuously differentiable random function defined wlog. on an interval and the corresponding the response. For simplicity we assume centered …
1.) Functional Principal Component Analysis Let be a centered smooth random function in , with finite second moment . Without loss of generality we assume instead of some arbitrary compact …