Chapter 7: Computer Vision with Convolutional Neural Networks

Activity 13: Amending our Model with Multiple Layers and Use of SoftMax

Solution:

1. Import the libraries and classes:

   #Import the Libraries

   from keras.models import Sequential from keras.layers import Conv2D from keras.layers import MaxPool2D from keras.layers import Flatten from keras.layers import Dense

2. Now, initiate the model with a Sequential class:

   #Initiate the classifier

   classifier=Sequential()

3. Add the first layer of the CNN, followed by the additional layers:

   classifier.add(Conv2D(32,3,3,input_shape=(64,64,3),activation=’relu’))

   classifier.add(Conv2D(32, (3, 3), activation = ‘relu’))

   classifier.add(Conv2D(32, (3, 3), activation = ‘relu’))

   32, (3,3) means that there are 32 feature detectors of size 3x3. As a best practice, always start with 32 and then you can add 64 or 128 later.

4. Now, add the pooling layer with an image size of 2x2:

   classifier.add(MaxPool2D(2,2))

5. The...