Given this data set, an

In this video I am going to define what is probably the most common type of machine

But we have to let the algorithm discover all this just from the data. Finally, it turns out that Unsupervised

learning. I'll define what these terms mean more in the next couple videos.

learning algorithms. There are several different types of learning algorithms.

Old Potions Master's habit, you know

My driving instructor says I should be more patient.

Let's show some examples of machine learning problems and I want you to tell me, for each one, whether it's best addressed with supervised learning, unsupervised learning, or reinforcement learning.

Peter will tell you some more about machine learning.

I learned nothing from the teacher.

We often just observe.

Every machine learning method is driven by some sort of target information that you care about.

I hope you have fun applying these methods in practice.

And one of the interesting aspects is that it's mainly for unsupervised problem, that there's some aspects of it that are also very similar to sort of the supervised learning problem.

So, congratulations.

Hey, hey, hey. What happened to you?

Teacher.

So I have a rat who is trained to press a lever to get a release of food when certain conditions are met.

By now, you see the range of different learning algorithms.

We talked a lot about supervised learning in which we are given data and target labels.

And these machine learning techniques are the enabling techniques that make that possible.

In this class we'll talk about supervised

And I'll talk about this when I talk about robotics in more detail.

And that's why the points plotted up on the figure don't have any labels on them.

learning problem, called Unsupervised Learning.

For each of the four check boxes on the left, check the ones for which you think Unsupervised Learning algorithm would be appropriate and then click the button on the lower right to check your answer.

And just to remind you the other most common type of supervised

But this was tedious work for the experts, so only a small number of states were labelled.

I'll give the materials, I'll come back and test them they get another zero,

Teacher.

I am a teacher. Ah ok

Meanwhile, I had grown up around a lot of teachers.

In both cases you're given data, but in 1 case you have labeled data, in another you have unlabeled data.

Ask Jeeves, etc.

And so I'd like to take the next videos to talk about that.

So we can apply that same process, even though it's not supervised.

Let's stop and review the 3 main forms of learning.

But each of these would be a fine example of a

And because there's a small number of discrete values, I would therefore treat it as a classification problem.

Next example is analyzing the spectral emissions of stars and trying to find clusters of stars in dissimilar types that may be of interest to astronomers.

I'm nothing but a poor teacher.

In this video, we'll talk about the second major type of machine

So, that's it for supervised learning and in the next video I'll talk about unsupervised learning, which is the other major category of learning algorithms.

I was a teacher.

Now this is a really complicated unsupervised