In this section, we will make predictions on the validation dataset. So far, machine learning hasn't been very helpful, because it has told us information about the training data that we already know. Let's have a look at the following steps:
- First, we will make predictions on the validation sets with the y_test and the X_test that we split out earlier.
- We'll do another for loop in for name, and model in models.
- Then, we will do the model.fit, and it will train it once again on the X and y training data. Since we want to make predictions, we're going to use the model to actually make a prediction about the X_test data.
- Once the model has been trained, we're going to use it to make a prediction. It will print ...
