Deep Learning Using Geometric Algebra

In the previous sections, we have presented different approaches for geometric neural computing and the Clifford support vector machines. Most of the cases are feed-forward network topologies involving just one hidden layer. So the next step is to extend the number of hidden layers to build more complex geometric neural networks for the so-called \(deep\,\,learning\) .