Python

In my previous blog post on reinforcement learning I demonstrated a way to get a gentle introduction into this field by using Keras-RL2. While writing that I found it quite difficult to get an overview of the many reinforcement learning frameworks available today which all have different levels of maturity.

The last few weeks I have been experimenting with deep neural networks for Reinforcement Learning. Reinforcement Learning is a way to learn to apply a sequence of events and has its root in control problems.

I recently had written a Python program to perform some performance calculations over the results from a regression model. The program was not too complex but the sheer number of calculations to be performed made it quite slow and resulted in a runtime of several hours.