I guess the model shown in this image (img_1)
is the same as the one in this image (img_2)
I was trying to build a neural net like that.
This keras code is to do the job.
model = Sequential() model.add(Dense(3, input_dim=3, activation='relu')) model.add(Dense(1, activation='sigmoid')) plot_model(model, to_file='model_plot.png', show_shapes=True, show_layer_names=True)
Model: "sequential_17" _________________________________________________________________ Layer (type) Output Shape Param # ================================================================= dense_31 (Dense) (None, 3) 12 _________________________________________________________________ dense_32 (Dense) (None, 1) 4 =================================================================
There are 3
ws and 1
b in the hidden layer. Why does this model have 12 parameters?