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Hello and welcome to this tutorial.

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Okay, we are almost ready to begin
our journey of data pre-processing,

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but first we need to get the data set.

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So that's what
we are going to do in this tutorial.

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So let's do this right now.

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And here it is just going to put
the column titles in bold okay.

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That's the data set.

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So what is this data set about.

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The data set contains
four columns country age

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salary and purchased and ten lines
ten observations.

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And basically this contains informations
of customers of some company.

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And the first three columns
are informations

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of these customers
like the country, the age and the salary.

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And the fourth column purchased here tells

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if yes or no, the customer
bought the product of the company.

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So we have to distinguish
something very important here

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that we will distinguish
for the rest of the course. It's

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the difference between the independent
variables and the dependent variables.

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So the independent variables are the first
three columns country age and salary.

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And the dependent variable
is purchased here the fourth column.

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And in any machine learning model
we are going to use

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some independent variables
to predict a dependent variable.

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So that means here that with the three
first columns,

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the three independent variables,
we are going to predict

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if yes or no,
the customer purchased a product okay.

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So that's the first distinction
that we really need to understand.

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And it's very important to do this section
because the data pre-processing steps

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that we're going to do in this section,

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we will have to do it for all the machine
learning models we are going to make.

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So it's really essential
to know how to manage this.

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But don't worry
it's going to be very simple.

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And besides, I'm going to give you
at the end of this section

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a template that will allow us later
to preprocess the data

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in a flashlight for all the machine
learning models we're going to make.

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So I look forward to starting the steps
with you.

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And until then, enjoy machine learning.