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…More
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…More
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…More
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…More
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…More
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…More
Why you need statistics to understand neuronal networks
When I tried to learn about neuronal networks first, I did what probably most of us would do – I started to look for tutorials, blogs etc. on the web and was surprised by the vast amount of resources that I found. Almost every blog or webpage about neuronal networks has a section on training…More
Mining bitcoins with Python
In this post, we will learn to build a very simple miner in Python. Of course this miner will be comparatively slow and limited and only be useful in our test network, but it will hopefully help to explain the principles behind mining. When we want to mine a block, we first need some information…More
The Metropolis-Hastings algorithm
In this post, we will investigate the Metropolis-Hastings algorithm, which is still one of the most popular algorithms in the field of Markov chain Monte Carlo methods, even though its first appearence (see [1]) happened in 1953, more than 60 years in the past. It does for instance appear on the CiSe top ten list…More
The difficulty in the bitcoin protocol
Mining is a challenge – a miner has to solve a mathematical puzzle to create a valid block and is rewarded with a certain bitcoin amount (12.5 at the time of writing) for investing electricity and computing power. But technology evolves, and the whole mining process would be pointless if the challenge could not be…More
LeftAsExercise 