Building a real-world image classifier with Transfer learning

In this case study, your company secured a medical project, and you are assigned the responsibility to build a pneumonia classifier for GETWELLAI. You have been provided with over 5,000 X-ray JPEG images, made up of two categories (pneumonia and normal). The dataset was annotated by expert physicians and low-quality images have been removed. Let's see how we can tackle this problem using the two types of transfer learning techniques we have discussed so far.

Loading the data

Perform the following steps to load the data:

1. As usual, we start by loading the necessary libraries that we will need for our project:

   #Import necessary libraries

   import os

   import pathlib

   import matplotlib.pyplot as plt

   import matplotlib.image as mpimg

   import random

   import numpy as np

   from PIL import Image

   import pandas as pd

   import tensorflow as tf

   from tensorflow import keras

   from tensorflow.keras.preprocessing.image import ImageDataGenerator...