Hi there. I have finally manage to be finishing the long series of posts about how to use random walk vectors for clustering problem. It’s been a long series and I am happy to finish it as the whole blog suddenly moved away from being about Julia and turned into a random walk weirdo… Anyways lets finish what has been started.

In the previous post we saw how to use many random walks to cluster given dataset. Presented approach was evaluated on toy datasets and our goal for this post is to try it on some more serious one. We will then apply same approach onto MNIST dataset – set of hardwritten digits images. We will compare the results to the state-of-the art k-means algorithm.

For the reminder of what is going to be applied – please take a step back to the previous post.