Math and Architectures of Deep Learning

7 Function approximation: How neural networks model the world

This chapter covers

• Expressing real-world problems as mathematical functions
• Understanding the building blocks of a neural network
• Approximating functions via neural networks

Computing to date has been dominated by the von Neumann architecture in which the processor and the program are separate. The program sits in memory and is fetched and executed by the processor. The advantage of this approach is that different programs solving unrelated problems can be loaded into memory, and the same processor can execute them. But neural networks have a fundamentally different architecture. There are no separate processors and programs; instead, there is a single entity called, well, the neural ...