Evaluating my model in new unseen dataset
If you want to get loss/accuracy or whatever other metrics you had during training - you need  .evaluate() method. If all you need is actual probabilities or regression values - you need .predict() method.
I have trained my model (.fit()) and satisfied with the performance on test split making prediction (.predict()). So I save my model to the disk (.save('model.h5')).
Now I'm given new unseen dataset and asked to evaluate my already saved model on this dataset for performance. I am required to not only report accuracy but stuff line precision/recall, confusion matrix etc...
I then loaded my saved model (.load_model('model.h5')).
Question:
What the appropriate function that I should use to prepare report of the model performance on this new dataset. I should I use .predict() function or .evaluate().