As an initial step, we import the required Python libraries (you can see this in the neural_machine_translation.py file):
import tensorflow as tfimport numpy as npfrom sklearn.model_selection import train_test_splitimport data_utilsimport matplotlib.pyplot as plt
tensorflow and numpy should already be familiar to you. matplotlib is a handy python library used for visualizing data (you will see how we use it shortly). Then, we use the train_test_split function of sklearn to split the data into random train and test arrays.
We also import data_utils, which is used to access the data collections mentioned in the previous section.
An important modification to do before splitting the data is making sure each ...
