The preparations

You will find the code for this example here: https://github.com/PacktPublishing/Interpretable-Machine-Learning-with-Python-2E/tree/main/13/Masks.ipynb

Loading the libraries

To run this example, you need to install the following libraries:

• mldatasets to load the dataset
• numpy and sklearn (scikit-learn) to manipulate it
• tensorflow to fit the models
• matplotlib and seaborn to visualize the interpretations

You should load all of them first:

import math
import os
import warnings
warnings.filterwarnings("ignore")
import mldatasets
import numpy as np
from sklearn import preprocessing
import tensorflow as tf
from tensorflow.keras.utils import get_file
import matplotlib.pyplot as plt
import seaborn as sns
from sklearn import metrics
from art.estimators.classification import KerasClassifier
from art.attacks.evasion import FastGradientMethod,\
                      ProjectedGradientDescent, BasicIterativeMethod
from...