Welcome back.
In our data set we have three columns origin one, origin two and origin three.
We get the standard deviation of those three columns.
Now let's get the means of those three columns.
So here let me scroll down.
You can see the origin is still one column.
We need the three columns.
So here origin one two and three.
So those are the columns one two and three.
Let's scroll down.
So here before feature scaling let me create and you code to get the mean of three columns.
Start with xtrain origin one two and three run.
And we get those numbers.
It's very simple.
We can get them from the X train because the X train contains the three columns origin one, two and
three.
Let me copy those values to here.
So copy this origin the second origin and the third origin okay.
Now our app is 99% ready.
Let me run.
This is our app for cylinders.
Displacement 150 horsepower 100 weight £3,000.
Acceleration 1576.
And American predict mpg.
And congratulations guys.
We get this predicted and correct mileage of our car.
Let me select European and predict.
And the European is better than American in terms of uh in terms of mileage.
And let's check Japanese.
Also Japanese is better than European and American origins.
Okay.
So this is our lovely application.
It's very, very interesting.
And by the way this is a complex application, not a simple application or simple ML application.
It's very important.
It's very complex.
And you learned a lot a lot of things and machine learning and Android integration.
Congratulations guys.
I hope see you in the next videos and next sections and next applications.