We now have a model that has been properly trained and selected among other models. We can use it to make predictions on new data.
Remember that, at the beginning of this chapter, under the section Loading the Data on S3, we uploaded two datasets to S3, the training dataset and the held-out dataset. We've used the training dataset to create the best model possible. We will now apply that model on the held-out dataset.
A batch prediction consists in applying a model to a datasource in order to make predictions on that datasource. We need to tell Amazon ML which model we want to apply on which data.
Batch predictions are different from streaming predictions. With batch predictions, all the data is already made available ...
