If we want to use our machine learning scripts in a production setting, there are some points we first need to consider as a best practice. In this section, we will outline some of them.
Taking TensorFlow to production
Getting ready
In this recipe, we want to summarize and condense various tips for bringing TensorFlow to production. We will cover how best to save and load vocabularies, graphs, variables, and model checkpoints. We will also talk about how to use TensorFlow's command-line argument parser and change TensorFlow's logging verbosity.