keras sequential model explained code example

Example 1: keras.sequential

from keras.models import Sequential
from keras.layers import Dense, Activation

model = Sequential([
    Dense(32, input_shape=(784,)),
    Activation('relu'),
    Dense(10),
    Activation('softmax'),
])

Example 2: keras declare sequential model

from keras.models import Sequential
from keras.layers import Dense
# NOTE: this is only how you declare a sequential model
# Declare a sequential model by adding layers to it
model = Sequential()
# Adding layer with size 2 and input dimensions 1
model.add(Dense(2, input_dim=1))
# Output size of the model will be the size of the last layer
model.add(Dense(1))
# This can also be done by passing the layers as an array
model2 = Sequential([Dense(2, input_dim=1), Dense(1)])
# or even a mixture of both
model2.add(Dense(1))