WEBVTT

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Welcome back.

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In our data set we have three columns origin one, origin two and origin three.

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We get the standard deviation of those three columns.

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Now let's get the means of those three columns.

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So here let me scroll down.

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You can see the origin is still one column.

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We need the three columns.

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So here origin one two and three.

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So those are the columns one two and three.

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Let's scroll down.

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So here before feature scaling let me create and you code to get the mean of three columns.

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Start with xtrain origin one two and three run.

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And we get those numbers.

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It's very simple.

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We can get them from the X train because the X train contains the three columns origin one, two and

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three.

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Let me copy those values to here.

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So copy this origin the second origin and the third origin okay.

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Now our app is 99% ready.

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Let me run.

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This is our app for cylinders.

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Displacement 150 horsepower 100 weight £3,000.

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Acceleration 1576.

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And American predict mpg.

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And congratulations guys.

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We get this predicted and correct mileage of our car.

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Let me select European and predict.

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And the European is better than American in terms of uh in terms of mileage.

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And let's check Japanese.

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Also Japanese is better than European and American origins.

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Okay.

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So this is our lovely application.

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It's very, very interesting.

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And by the way this is a complex application, not a simple application or simple ML application.

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It's very important.

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It's very complex.

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And you learned a lot a lot of things and machine learning and Android integration.

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Congratulations guys.

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I hope see you in the next videos and next sections and next applications.