Build Sequential Neural Network Keras

gistfile1.txt

# Build sequential neural network

model = keras.models.Sequential()  # Keras sequential model is composed of a single stack of layers connected sequentially
model.add(keras.layers.Input(shape=(784)))  # Input layer is a 1D array (no parameters, first layer so specify input shape, not including batch size just size of instances)
model.add(keras.layers.Dense(300, activation="relu"))  # Dense hidden layer with 300 neurons and ReLU activation fucntion ( each dense layer manages it's own weight matrix and bias vector)
model.add(keras.layers.Dense(100, activation="relu"))  # Second Dense hidden layer of 100 neurons
model.add(keras.layers.Dense(10, activation="softmax"))  # Final layer is a dense output layer of 10 neurons with softmax activation function (there are 10 exxclusive classes)

# Displays all the model's layers 
model.summary()