Hello and welcome to this new section on classification.
Very exciting.
Classification is a very popular and important tool in machine learning.
So I'm super excited to get started.
Let's have a look.
All right.
So classification can be defined as a machine learning technique to
identify the category of new observations based on training data.
this is different to regression where we had to predict a continuous number.
Here we use classification to predict a category.
Another important thing is that it's a type of supervised learning algorithm.
We'll discuss this a bit more when we reach the next section on clustering.
And there are actually a variety of applications of classification
from medicine to marketing to business and lots of different areas.
Let's have a look at a few.
So for example, you have customers of a business
and you would like to predict which ones are likely to stay
and which ones are likely to leave.
This is also called churn modeling.
Very important
because if you can predict which customers are likely to leave
your business in the next month or six months, then you can take actions
and send them special offers, or ask them about their feedback
and make certain changes so that they stay.
So it's, very powerful tool for businesses.
Another application is, email.
So for instance, if you get an email, it might be classified
as normal mail or it might be classified as important an urgent mail.
It might have a special marker, especially if using Gmail.
You'll see those little, chevrons
or triangles at the beginning of a message saying that it's important.
Or it might be categorized as a promotion and it might be put into a
separate folder.
So it's not a filling up your main, inbox which you use for work.
Or it might be categorized as spam.
So spam filters have become very good.
over the past few years, we barely see any spam in our inboxes.
and that is thanks to classification algorithms.
And another, application is image recognition.
so, for instance, here we have images of dogs and cats.
classification would be able to separate dogs, from cats.
So those are just a few examples.
As you can see, it's a very powerful tool.
There are lots of algorithms that fall into this family of classification
in machine learning, and they have a variety of applications.
So I'm very excited to explore this section further with you together.
And until next time, enjoy machine learning.