Convolutional Layer 1
model.add(Conv2D(64 (3, 3), input_shape = (150, 150, 3), activation = 'relu'))
model.add(MaxPooling2D(pool_size = (2, 2)))
```
**# Convolutional Layer 2** model.add(Conv2D(64, (3, 3), activation = 'relu')) model.add(MaxPooling2D(pool\_size = (2, 2)))

The convolutional network helps to extract features from the image and digit 64 means to extract 64 features.

model.add(Flatten())

**# Hidden Layer 1** model.add(Dense(units = 64, activation = 'relu'))

```