Testing your model
During training, you apply the model to known data to adjust the settings to improve the results. When your results are good enough for the needs of your application, you should deploy the model to whatever system your application uses and test it.
To test your model, run data through it in a context as close as possible to your final application and your production infrastructure.
Use a different dataset from those used for training and evaluation. Ideally, you should use a separate set of data each time you test, so that your model is tested with data that it has never processed before.
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