Before we start learning about the data, let's split it into a training set and a test set.
First, let's import Numpy:
import << your code goes here >> as np
Then, import train_test_split from sklearn:
from sklearn.model_selection import << your code goes here >>
Now let's collate the data in X and y variables:
X = np.array(ham_emails + spam_emails)
y = np.array([0] * len(ham_emails) + [1] * len(spam_emails))
Finally, let's split the dataset into a 80/20 ratio:
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=<< your code goes here >>, random_state=42)
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