Monte Carlo methods and Markov chains – an introduction

In our short series on machine learning, we have already applied sampling methods several times. We have used and implemented Gibbs sampling, and so far we have simply accepted that the approach works. Time to look at this in a bit more detail in order to understand why it works and what the limitations of … Continue reading Monte Carlo methods and Markov chains – an introduction

Training a restricted Boltzmann machine on a GPU with TensorFlow

During the second half of the last decade, researchers have started to exploit the impressive capabilities of graphical processing units (GPUs) to speed up the execution of various machine learning algorithms (see for instance [1] and [2] and the references therein). Compared to a standard CPU, modern GPUs offer a breathtaking degree of parallelization - … Continue reading Training a restricted Boltzmann machine on a GPU with TensorFlow

Creating and signing a bitcoin transaction from scratch

In the one of the the last posts in this series, we have been able to successfully verify an existing bitcoin transaction. With the understanding of how this works, we should now be able to conversely create a transaction from scratch, sign it and publish it in the bitcoin network. Given an amount that we … Continue reading Creating and signing a bitcoin transaction from scratch