[D] Do neural networks create a separating hyperplane?

[https://colah.github.io/posts/2014-03-NN-Manifolds-Topology/](https://colah.github.io/posts/2014-03-NN-Manifolds-Topology/) mentions that neural networks learn a representation of the data so as to make the classes linearly separable. What I fail to see is how does a neural network create a separating hyperplane that separates the classes. How do we know that it creates a hyperplane? What's the math behind it?

hyperplane machinelearning networks neural networks