"""\nCreate a Multilayer Perceptron (MLP) Neural Network with three inputs and one output.\n"""\n\nimport keras\nfrom keras.models import Sequential\nfrom keras.layers import Dense\n\n# define the model\nmodel = Sequential()\nmodel.add(Dense(12, input_dim=3, activation=\relu\))\nmodel.add(Dense(1, activation=\sigmoid\))\n\n# compile the model\nmodel.compile(loss=\binary_crossentropy\, optimizer=\adam\, metrics=[\accuracy\])\n\n# summarize the model\nmodel.summary()
Create a Multilayer Perceptron (MLP) Neural Network with three inputs and one output that can predict an output based on the input variables.?