Week 3 assignment - meaning of decision boundary - graph before running model

Course Q&A Deep Learning Specialization Neural Networks and Deep Learning
1

I’m trying to figure out the meaning of the decision boundary graphs. Wanted to understand if the lines were a function of the model parameters or something imagined by the function def plot_decision_boundary(model, X, y):. So I ran the function after initializing the parameters to random numbers but before the first pass through the NN model. It still gave me a decision boundary even with random numbers in W1, W2 and zeros in b1, b2.

Please help explain where those boundaries come from.

Week 3_150_unit_layer before first pass

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The decision boundaries are the results of the model with whatever the particular model parameters are at the point that you call plot_decision_boundary. You can examine the logic of that function by clicking “File → Open” and having a look around. Examine the “import” cell at the beginning of the notebook in order to know what file to open.

This is the key matplotlib function used to create the decision boundary graph.