Python Deep Learning Projects

Compiling the model

We need to define and compile the deep convolution model like so:

# define modelmodel = Sequential()model.add(Conv2D(32, kernel_size=(3,3), input_shape=input_shape, activation = 'relu'))model.add(MaxPool2D(2,2))model.add(Dropout(0.2))model.add(Conv2D(64, kernel_size=(3,3), activation = 'relu'))model.add(MaxPool2D(2,2))model.add(Dropout(0.2))model.add(Conv2D(128, kernel_size=(3,3), activation = 'relu'))model.add(MaxPool2D(2,2))model.add(Dropout(0.2))model.add(Flatten())model.add(Dense(128, activation = 'relu'))model.add(Dropout(0.2))model.add(Dense(10, activation = 'softmax'))# compile modelmodel.compile(loss = 'sparse_categorical_crossentropy', optimizer= optimizer, metrics = ['accuracy'])