Clustering via mutual information maximization. Part 1

In this series of posts we will learn logistic regression classifier in three ways: supervised, unsupervised and something in between. We will find out that for some machine learning problems you need only a few labels for your data to get a decent model. Continue reading Clustering via mutual information maximization. Part 1

Prediction of random numbers. Part 2

In the first part of this post we considered a human-based binary random numbers generator and built a predictive model for it. The model appeared to work better than a coin toss, at least for a short sequence we had. This part develops more complex models with somewhat higher accuracy. Continue reading Prediction of random numbers. Part 2