Hello and welcome to this tutorial.
Okay, we are almost ready to begin our journey of data pre-processing,
but first we need to get the data set.
So that's what we are going to do in this tutorial.
So let's do this right now.
And here it is just going to put the column titles in bold okay.
That's the data set.
So what is this data set about.
The data set contains four columns country age
salary and purchased and ten lines ten observations.
And basically this contains informations of customers of some company.
And the first three columns are informations
of these customers like the country, the age and the salary.
And the fourth column purchased here tells
if yes or no, the customer bought the product of the company.
So we have to distinguish something very important here
that we will distinguish for the rest of the course. It's
the difference between the independent variables and the dependent variables.
So the independent variables are the first three columns country age and salary.
And the dependent variable is purchased here the fourth column.
And in any machine learning model we are going to use
some independent variables to predict a dependent variable.
So that means here that with the three first columns,
the three independent variables, we are going to predict
if yes or no, the customer purchased a product okay.
So that's the first distinction that we really need to understand.
And it's very important to do this section because the data pre-processing steps
that we're going to do in this section,
we will have to do it for all the machine learning models we are going to make.
So it's really essential to know how to manage this.
But don't worry it's going to be very simple.
And besides, I'm going to give you at the end of this section
a template that will allow us later to preprocess the data
in a flashlight for all the machine learning models we're going to make.
So I look forward to starting the steps with you.
And until then, enjoy machine learning.