Original subtitles

Hello and welcome back to the course on machine learning in today's tutorial We will show you how to

download the data sets for this course.

Now as you can probably tell the courses large has got to over 200 tutorials and over 35 hours of content.

And as you can imagine that much training we will have to have lots and lots of data sets and that's

why we have decided to place all of the data centers on their own separate page.

So in order to get the data sets you will need to go to W.W. does super data science dot com slash machine

high from learning.

So that's two words machine high and learning.

The website is super data centers dot com.

And here you'll see a whole page dedicated to this course with lots and lots of data sets available

which you can download and install onto your machine in order to fall along with the tutorials.

So today we're going to start off with the very first one as an example and then throughout the course

you'll be able to download the right data set for every single session.

Depending on the session that you're doing.

So today we're going to start off with the data pre-processing data set.

And here also we are going to get right away the machine learning it is that template folder is a special

template folder we've created for you to help you store these data sets in a hierarchical fashion so

that you can navigate all of these datasets better and that's so that they're all in the right place

so we have a very orderly folder structure on your own machine.

So go ahead and download these to the above zip files.

So if you just click there and click there you'll see that these are being downloaded.

The first one is very small is just empty folders.

And then the second one is the data set for the section and then whenever you get to a new section we'll

of course remind you at the start of the section.

But basically what you'll need to do is just download the right data set for your section that you're

in but more on that later.

Let's move on to today's section.

So we've got these two zip files here.

All you have to do is take the machine learning what is a template folder and unzip it to the location

where you want it to be.

So I'll get on Zip mind to the desktop I'm going to right click and I'm going to extract just click

effect here.

So that's on Windows on Mac.

Similar thing just open unzip the file and zip zip folder.

So there we go there's a folder.

And now if you look inside here you'll see that you've got a very nice neat structure.

You can go inside any one of these sections for instance clustering you'll see the title of the section

and then you can go into any one of these.

And again these are empty for now and that's because we haven't done those sections as you go through

the course you will populate these folders with their respective data sets.

Now we're going to go into data pre-processing so part 1.

And here we've got this whole empty folder so we don't worry about the folders with the dashes those

are just titles to remind us where we're located inside the folder structure.

So just go ahead and take your data pre-processing zip folder drag it here and right click and just

say extract action here.

And again just go inside to pre-processing because we don't want it to be in its own separate folder.

Just take all these files.

Copy that was right click.

Actually cut them and then paste them here.

So basically you don't need this folder now because it's empty.

Delete that folder.

You can delete the zip file because we don't need it anymore and you can delete the zip file as well.

So there we go.

Now we have our machine learning aitches a template folder.

You can remove sheilas do that we can remove template folder from there and just say machine learning

to read.

And if you go in here you'll see data pre-processing and there you go see you've got your data set ready

for the session plus you really have all of the templates which you will be creating with Hoddle and

throughout the tutorials in this section.

So that's pretty much what you need to do for every single section that you go through.

And again I will remind you and the reason for the structure is so what why did we structure it like

this.

Why did we for instance not include all of the data sets right away inside these folders for you right.

That would looks feels like it would be more convenient but at the same time there's a couple of reasons

so the first one is that in case we need to update something in case we need to update a certain section

like this section for instance we need to update the dataset.

Well in that case if we had to update it and then upload the whole folder that would take time.

That would mean the Course would not be available for longer or that means while we're updating a lot

of people we'll be getting the wrong data set and we don't want that so if we want to update something

now we can very quickly just update that one zip file on the Web site and that's very very quick for

us to do.

And the second reason is of course size if we had put all of the datasets in here right away this fall

there would be massive.

So it's a much more efficient to download just a section that you're doing and then proceed with those

tutorials.

So there we go.

That's how you get the data set.

And now I'll hand you over to her son who'll take you through two days of data set.

So what does this data set about this virus that contains Arkan's country age salary and purchased and

10 10 months 10 observations and basically this contains information 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 sells.

If yes or no the customer but 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 or any model we are going to use some independent variables to

predict a dependent variable.

So that means here that with this 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 into 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 fleshlight 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.