So this is a bit of a Venn diagram here in Goodfellow's book,

Deep Learning, and this probably looks like an eye chart,

but you can look at the slides later.

So as we move from the outside here, we've got example of

knowledge bases, or you can think about them as facts or

places where you can go look up information.

And we have very simple examples in this next ring here of logistic regression or

linear regression.

And then this is where machine learning begins.

And then there's a more complicated set of

algorithms and an example in this more inner.

And the ones in here are called representation learning.

An example is called the shallow autoencoder.

And then we have what's called deep learning.

And here, you'll see this term all the time now, everyone's doing deep learning.

And they're doing deep learning because it's working and

solving certain types of classes of problems.

Is it conscious?

No, it's not conscious.

So shallow autoencoder is a neural network that finds structure in data.

And then MLP stands for multi-layer perception, or

a more complex neural network.