lesson 1

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• Import the Sequential model and Dense layer from keras.models import Sequential from keras.layers import Dense

• Create a Sequential model model = Sequential()

• Add an input layer and a hidden layer with 10 neurons model.add(Dense(10, input_shape=(2,), activation="relu"))

• Add a 1-neuron output layer model.add(Dense(1))

• Summarise your model model.summary()

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Intor_keras.pdf

ppt

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Instantiate a Sequential model. Add a Dense layer of 50 neurons with an input shape of 1 neuron. Add two Dense layers of 50 neurons each and 'relu' activation. End your model with a Dense layer with a single neuron and no activation.

Instantiate a Sequential model

model = Sequential()

Add a Dense layer with 50 neurons and an input of 1 neuron

model.add(Dense(50, input_shape=(1,), activation='relu'))

Add two Dense layers with 50 neurons and relu activation

model.add(Dense(50,input_shape=(50,), activation='relu')) model.add(Dense(50,input_shape=(50,), activation='relu'))

End your model with a Dense layer and no activation

model.add(Dense(1))

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