How to Implement a Python Script to Improve Your Predictions?

The framework that we have here is strictly research sly. This is not a production you can't deploy what we're doing in production. All this is is something that will take your model on an off line data set and allow you to improve it. The main things you need are a supernaneta, sampled architecture implemented, which you probably already have. And do you have any observations from the training of your own model? What should one expect in terms of the rate of learning? And when it converges in all those important details.