They are called semi supervised or self supervised, and they use elements of unsupervised learning and pair them with supervised learning.

So for each example in Supervised

Is that supervised, unsupervised or reinforcement?

learning problem, which is supervised learning.

Would that be supervised, unsupervised or reinforcement?

Is that supervised, unsupervised or reinforcement learning?

In this class we'll talk about supervised

So here's how this supervised learning algorithm works.

In the last video, we talked about Supervised Learning.

The supervised learning paradigm is the dominant paradigm in machine learning, and there are a vast amount of papers being written about it.

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Within supervised learning, the performance of many supervised learning algorithms will be pretty similar and when that is less more often be whether you use

In between, there are techniques that do both supervised and unsupervised.

So this is an example of a supervised learning algorithm. And it's supervised learning because we're given the, quotes, right answer for each of our examples.

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

The main two types are what we call supervised learning and unsupervised

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

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learning algorithm. So this is an example of a supervised learning algorithm.

But for the time being, understand that the paradigms supervised and unsupervised span 2 very large areas of machine learning, and you learn quite a bit about it.

Support vector machines are supervised learning models used for classification and regression analysis.

I'd like to say a few final words about supervised versus unsupervised learning.

We talked about classification and regression and different methods to do supervised learning.

And yes, Supervised Learning algorithm may break these data into these two separate clusters.

Consider a supervised learning classification problem where you have a training set like this.

Let me back up a step further, and let's look at supervised learning more generally.

Here's another supervised learning example, some friends and I were actually working on this earlier.

So, it facilitates outpatient care which is obviously much cheaper than any type of supervised care.

learning at the beginning of the class but it's useful to contrast it with supervised learning.

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

We have supervised learning, in which the training set is a bunch of input output pairs

A man had inevitably supervised to make sure it'll be sh tty from the beggining to the end!

The program tried to generalize from that, using supervised learning, and was not able to perform very well.

And that looks just like what we did when we used supervised machine learning to update our waits.

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The supervised learning problem in this case is given a set of labels to fit a hypothesis to it.

More formally, in supervised learning, we have a data set and this data set is called a training set.

In the next video, I'm going to define what is supervised learning and after that, what is unsupervised learning.

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I've personally supervised the investment of tens of millions of dollars into companies who have pitched me with PowerPoint presentations.

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