Recently, I picked up an old project of mine - implementing a Unix like operating kernel from scratch. I will post more on this later, but one of the first things I stumbled across when browsing my old code and my old documentation was the networking stack. I used this as an opportunity to refresh … Continue reading Networking basics – the layered networking model

# More on Paperspace Gradient

Its been a few days since I started to play with Paperspace, and I have come across a couple of interesting features that the platform has - enough for a second post on this topic. First, GIT integration. Recall that the usual process is to zip the current working directory and submit the resulting file … Continue reading More on Paperspace Gradient

# First steps with Paperspace Gradient

So far, I have exclusively been using AWS EC2 when I needed access to a GPU - not because I have carefully compared the available offerings and taken a deliberate decision, but simply because I already had an EC2 account and know the platform. However, I though it would be interesting to try out other … Continue reading First steps with Paperspace Gradient

# The EM algorithm and Gaussian mixture models – part II

In this post, I will discuss the general form of the EM algorithm to obtain a maximum likelihood estimator for a model with latent variables. First, let us describe our model. We suppose that we are given some joint distribution of a random variable X (the observed variables) and and random variable Z (the latent … Continue reading The EM algorithm and Gaussian mixture models – part II

# The EM algorithm and Gaussian mixture models – part I

In the last few posts on machine learning, we have looked in detail at restricted Boltzmann machines. RBMs are a prime example for unsupervised learning - they learn a given distribution and are able to extract features from a data set, without the need to label the data upfront. However, there are of course many … Continue reading The EM algorithm and Gaussian mixture models – part I

# Controlling Docker container with Python

In the last few posts on the bitcoin blockchain, I have already extensively used Docker container to quickly set up test environments. However, it turned out to be a bit tiresome to run the containers, attach to them, execute commands etc. to get into a defined state. Time to learn how this can be automated … Continue reading Controlling Docker container with Python

# How the number of bitcoins is limited

In some of the previous posts, we did already hit upon the file chainparams.cpp in the source code of the bitcoin reference client. It is interesting to go through this and understand the meaning of the various parameters defined there. One of them should catch your attention: What does this parameter mean? It is in … Continue reading How the number of bitcoins is limited