In Chapter 2, we did some amazing things with one neuron, but that is hardly flexible enough to tackle more complex cases. The real power of neural networks comes to light when several (thousand, even million) neurons interact with each other to solve a specific problem. The network architecture (how neurons are connected to each other, how they behave, and so on) plays a crucial role in how efficient the learning of a network is, how good its predictions are, and what kind of problems it can solve.
There are many kinds of architectures that have been extensively ...
