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Hello and welcome to this new section
on classification.

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Very exciting.

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Classification is a very popular
and important tool in machine learning.

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So I'm super excited to get started.

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Let's have a look.

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All right.

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So classification can be defined
as a machine learning technique to

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identify the category of new observations
based on training data.

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this is different to regression where
we had to predict a continuous number.

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Here we use classification
to predict a category.

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Another important thing is that it's
a type of supervised learning algorithm.

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We'll discuss this a bit more when we
reach the next section on clustering.

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And there are actually a variety
of applications of classification

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from medicine to marketing to business
and lots of different areas.

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Let's have a look at a few.

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So for example,
you have customers of a business

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and you would like to predict
which ones are likely to stay

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and which ones are likely to leave.

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This is also called churn modeling.

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Very important

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because if you can predict
which customers are likely to leave

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your business in the next month
or six months, then you can take actions

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and send them special offers,
or ask them about their feedback

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and make certain changes
so that they stay.

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So it's, 
very powerful tool for businesses.

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Another application is, email.

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So for instance, if you get an email,
it might be classified

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as normal mail or it might be classified
as important an urgent mail.

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It might have a special marker,
especially if using Gmail.

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You'll see those little, chevrons

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or triangles at the beginning of a message
saying that it's important.

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Or it might be categorized as a promotion
and it might be put into a

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separate folder.

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So it's not a filling up your main, inbox
which you use for work.

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Or it might be categorized as spam.

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So spam filters have become very good.

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over the past few years,
we barely see any spam in our inboxes.

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and that is thanks to classification
algorithms.

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And another,
application is image recognition.

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so, for instance, here
we have images of dogs and cats.

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classification
would be able to separate dogs, from cats.

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So those are just a few examples.

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As you can see, it's a very powerful tool.

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There are lots of algorithms that fall
into this family of classification

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in machine learning,
and they have a variety of applications.

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So I'm very excited to explore
this section further with you together.

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And until next
time, enjoy machine learning.