These are codes I used through Python to try neural networks to find the predicted revenue based on these predictors. When I tried to fit the model, I got the following error: ValueError: Exception encountered when calling Sequential.call(). Input 0 of layer "dense_2" is incompatible with the layer: expected axis -1 of input shape to have value 3, but received input with shape (None, 14) Arguments received by Sequential.call(): • inputs=tf.Tensor(shape=(None, 14), dtype=float32) • training=True • mask=None I already knew that the problem that needs to be resolved is to reshape the NumPy array to a 2 dimensional array or add a second dimension to the data. I tried the functions .reshape(-1,1) and np.expand_dims but nothing seems to be working Does anyone know on how to rectify this problem? Thank you very much. Continue reading...
