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Lines 21-23 define a simple 32-8-4 network using Keras’ functional API. ![]() Here you can see we are defining two inputs to our Keras neural network: # our model will accept the inputs of the two branches and Z = Dense(2, activation="relu")(combined) # apply a FC layer and then a regression prediction on the # the second branch opreates on the second inputĬombined = concatenate() # the first branch operates on the first input USE MULTIBLE INPUTES TO GRANDTOTAL CODETo see the power of Keras’ function API consider the following code where we create a model that accepts multiple inputs: # define two sets of inputs Notice how we are no longer relying on the Sequential class. We can define the sample neural network using the functional API: inputs = Input(shape=(10,)) This network is a simple feedforward neural without with 10 inputs, a first hidden layer with 8 nodes, a second hidden layer with 4 nodes, and a final output layer used for regression. Model.add(Dense(8, input_shape=(10,), activation="relu"))
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