## Convolutional Neural Networks

**Convolutional Neural Networks**, **ConvNets**, or **CNNs** for short, are the driving engine behind computer vision. ConvNets allow us to work with larger images while still keeping the network at a reasonable size.

The name Convolutional Neural Network comes from the mathematical operation that differentiates them from regular neural networks. Convolution is the mathematically correct term for sliding one matrix over another matrix. We'll explore in the next section, *Filters on MNIST*, why this is important for ConvNets, but also why this is not the best name in the world for them, and why ConvNets should, in reality, be called **filter nets**.

You may be asking, "but why filter nets?" The answer is simply because what makes them work is the fact that they use filters.

In the next section, we will be working with the MNIST dataset, which is a collection of handwritten digits that has become a standard "Hello, World!" application for computer vision.

### Filters on MNIST

What does...