I love building things. This blog in itself is one of these things. Feel free to shoot me an email.
Posts
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Clustering - k-means & SOM
Chapters General Terms and tools PCA PCA Hebbian Learning Kernel-PCA Source Separation ICA Infomax ICA Second Order Source Separation FastICA Stochastic Optimization Clustering k-means Clustering Pairwise Clustering Self-Organising Maps Locally Linear Embedding Estimation Theory Density Estimation Kernel Density Estimation Parametric Density Estimation Mixture Models - Estimation Models K-means Clustering K-means Clustering is good at finding equally sized clusters of data points. Parameters Distance Function (Usually Euclidean) Number of clusters Drawbacks...
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Source Separation (ICA)
Chapters General Terms and tools PCA PCA Hebbian Learning Kernel-PCA Source Separation ICA Infomax ICA Second Order Source Separation FastICA Stochastic Optimization Clustering k-means Clustering Pairwise Clustering Self-Organising Maps Locally Linear Embedding Estimation Theory Density Estimation Kernel Density Estimation Parametric Density Estimation Mixture Models - Estimation Models Independent Component Analysis (ICA) ICA allows the reconstruction of mixed signals. This could for example be multiple speakers on one audio track. Requirements...
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PCA
Chapters General Terms and tools PCA PCA Hebbian Learning Kernel-PCA Source Separation ICA Infomax ICA Second Order Source Separation FastICA Stochastic Optimization Clustering k-means Clustering Pairwise Clustering Self-Organising Maps Locally Linear Embedding Estimation Theory Density Estimation Kernel Density Estimation Parametric Density Estimation Mixture Models - Estimation Models PCA can be used as a compression algorithm(more correctly dimensionality reduction). Its goal is to extract vectors(components) out of the sample data which...
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Unsupervised Learning Methods Exam Preparation
Following the principle “You only understood something thoroughly if you can explain it” - here come the prepping notes for Machine Intelligence II. If no sources are indicated, it comes from the lecture slides. Note This was foremostly written for my own understanding, so it might contain incomplete explanations Chapters General Terms and tools PCA PCA Hebbian Learning Kernel-PCA Source Separation ICA Infomax ICA Second Order Source Separation FastICA Stochastic...
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DocumentDeck
Today I am excited to announce the launch of DocumentDeck. DocumentDeck solves my own problem with keeping track of invoices and credentials. The documents I receive usually end up on a large pile on my desk or in a huge binder if I have my lucky day. Now I have an easy way of just scanning the documents and having them easily retrievable in the future. Uploading is as easy...
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How to serve a website from behind a NAT with a VPS
A common way to run a website behind a NAT as you might find it at home is to configure the router to forward port 80 to your machine. This is not always doable, as you might not have access to the router. If you have access to an external server(for example a cheap VPS), you can route traffic through that by connecting to it via SSH from the local...
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Introducing Kudos
Kudos is a way to acknowledge something somewhat similar to a “like”. Each of my blog posts now has a kudos button at the bottom. I liked the simplicity of it. I use a nice libary from KudosPlease which looks quite slick. Unfortunately the API provided by them had multi-second load time. Now I run my own fast compatible API at https://kudos.niels-ole.com/ . You can find the backend source on...
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Hosting side-projects with Docker
In this article I will write about: Why I needed a new hosting setup for my projects Make a shallow dive into why I chose Docker Show great tools for easy deployments for HTTP(S) List services running with this now I regularly do side-projects which mostly consist of some API or website of some sorts. After developing it locally I have to deploy it to a server to make it...
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