1

00:00:08,000 --> 00:00:12,920

Hey guys this is Caleb with Dev slopes and I just wanted to show you really quickly before we get started



2

00:00:13,010 --> 00:00:15,380

what kind of an app are you going to build in this car.



3

00:00:15,420 --> 00:00:17,450

M.S. So here it is.



4

00:00:17,450 --> 00:00:19,890

This is the app we're going to build it's running on my phone.



5

00:00:19,910 --> 00:00:25,370

So I'm using the camera here because the simulator does not have a camera so we can actually use the



6

00:00:25,370 --> 00:00:31,550

simulator with that in mind you're going to need a physical device plugged into your computer to build



7

00:00:31,550 --> 00:00:35,450

your app and actually in X code 9 you can build over Wi-Fi which is really cool.



8

00:00:35,450 --> 00:00:40,730

Finally Anyway I just wanted to show you this application what it does is it displays the camera view.



9

00:00:40,790 --> 00:00:46,670

We have a label up here that basically is going to display the name of an object and the level of confidence



10

00:00:46,790 --> 00:00:48,220

which I'll explain in a second.



11

00:00:48,230 --> 00:00:53,990

We have a button that allows us to turn on or turn off the flash and when we tap on the screen that's



12

00:00:53,990 --> 00:01:01,130

going to take a photo and pass that photo through a memory sorry through a machine learning model and



13

00:01:01,130 --> 00:01:06,620

it's going to make a prediction of what it thinks that object is we're doing object scanning object



14

00:01:06,620 --> 00:01:09,060

recognition with machine learning in an iOS app.



15

00:01:09,080 --> 00:01:09,880

It's incredible.



16

00:01:09,920 --> 00:01:12,030

So here's an example if I take a photo.



17

00:01:12,050 --> 00:01:17,240

Listen carefully.



18

00:01:18,840 --> 00:01:19,490

Pretty cool.



19

00:01:19,490 --> 00:01:22,130

So it's 99 percent sure this is a remote.



20

00:01:22,140 --> 00:01:29,190

Based on how it was trained to identify a remote it can identify all kinds of objects trees window shades



21

00:01:29,190 --> 00:01:31,270

light switches umbrellas et cetera et cetera.



22

00:01:31,410 --> 00:01:36,270

It can identify all of it that's the coolest part about machine learning is that somebody else has trained



23

00:01:36,270 --> 00:01:38,810

this model to do all the amazing things it can do.



24

00:01:38,820 --> 00:01:40,800

So let's go ahead and let's dive right in.



25

00:01:40,800 --> 00:01:43,360

Head over to the next video and we'll get started building this app.