Created on 11-14-201805:02 AM - edited 08-19-201901:31 PM
In part 1 of, we looked at how we could use deep learning to classify Melanoma, using transfer learning with a pre-trained VGG16 convolutional neural network. Here we take a look at how to implement this using TensorFlow and Keras.
First we import the packages we need:
import numpy as np
from keras.preprocessing.image import ImageDataGenerator
from keras.models import Sequential
from keras.layers import Dropout, Flatten, Dense
from keras import applications
These packages include, the network layers we will be using, the applications (which includes the pretrained VGG16 model), and some image pre-processing utilities.
Next, we “strip” our model of it’s top layers. This is as simple as one line of code in Keras.