Hyperparameter optimization for Neural Networks -- NeuPy

The idea is similar to Grid Search, but instead of trying all possible combinations we will just use randomly selected subset of the parameters. Instead of trying to check 100,000 samples we can check only 1,000 of parameters. Now it should take a week to run hyperparameter optimization instead of 2 years. Let's sample 100 two-dimensional data points from a uniform distribution. In case if there are not enough data points, random sampling doesn't fully covers parameter space.