How does one deploy a model, after building it in Python or Matlab?
what comes after training a model is persisting (in layman terms, saving) a model, if you want to save the parameters for later deployment. 

All companies that do serious machine learning spend many hours (sometimes even days or weeks) training the models. Obviously, when you need rapid predictions in a deployment mode, you use a pre-trained model to generate said prediction.

In python, for example, there are a number of way to persist models. The most common libraries used are pickle and cpickle (i/o much faster I believe as the core is in C).

Here is a link to model persistence in sklearn:

http://scikit-learn.org/stable/modules/model_persistence.html