Importing the dependencies

We will be using numpy, matplotlib, keras, tensorflow, and the tqdm package in this exercise. Here, TensorFlow is used as the backend for Keras. You can install these packages with pip. For the MNIST data, we will be using the dataset that's available in the keras module with a simple import:

import matplotlib.pyplot as plt
%matplotlib inline

import os
import random
import glob
import h5py
from scipy.io import loadmat
import numpy as np
import pandas as pd
import cv2 as cv
from __future__ import print_function

from sklearn.model_selection import train_test_split

from keras.models import Sequential, Model
from keras.layers.core import Flatten, Dense, Dropout
from keras.optimizers import Adam
from keras import backend as K
from keras import applications
K.clear_session()

It is important that you set seed for reproducibility:

# set seed for reproducibility
seed_val...