neural = {
          net : new convnetjs.Net(),
          layer_defs : [
            {type:'input', out_sx:4, out_sy:4, out_depth:1},
            {type:'fc', num_neurons:25, activation:"regression"},
            {type:'regression', num_neurons:5}
          ],
          neuralDepth: 1
      }

#---Build Model-----
    model = models.Sequential()
    # Input - Layer
    model.add(layers.Dense(4, activation = "relu", input_shape=(4,)))
    # Hidden - Layers
    model.add(layers.Dense(25, activation = "relu"))
    model.add(layers.Dense(5, activation = "relu"))
    # Output- Layer
    model.add(layers.Dense(1, activation = "linear"))
    model.summary()
    # Compile Model
    model.compile(loss= "mean_squared_error" , optimizer="adam", metrics=["mean_squared_error"])