Machine Learning for Mobile

Defining the model's architecture

Once the data preparation is completed, the next step is to define the model and create it, so let's create the model:

model_m = Sequential()

The preceding line will create a sequential model that will process the layers in the sequential way they are arranged. There are two ways to build Keras models, sequential and functional:

• The sequential API: This allows us to create models layer-by-layer. Through this, we cannot create models that share layers or have multiple input or output.
• The functional API: This allows us to create models that are more than and can have complex connection layers—you can literally connect from any layer to any other layer:

model_m.add(Conv2D(32, (5, 5), input_shape=(1,28,28), ...