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So it looks like my file is completely uploaded because this number hasn't gone up in a little while.

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And now you may notice a little discrepancy between what the file appears to be in size here on my local

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machine seven twenty four point five and six ninety one.

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Mm hmm.

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But this has seven twenty four four hundred ninety five thousand nine hundred twenty six bytes which

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equates to that.

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So then maybe a little bit of a discrepancy in terms of how Google Drive Stores files compared to locally

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and how it represents size but it looks like all of the files of uploaded which is what we're after.

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So now we've got our zip file and our dog vision folder on our Google Drive.

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The next step is to unzip it much like we could locally.

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So if I just double click here it's going to expand dog breed ID dot zip.

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So we'll have a look at what's inside

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Beautiful.

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So this is what we're off to try and test sample submission labels dot CSB and this is what Kaggle says

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it's gonna give us if we were to download the zip labels sample submission test and train and in labels

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we have ten thousand two hundred twenty two unique values.

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OK.

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Wonderful.

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So these are the kind of things that we can test to make sure that even if we see a little discrepancy

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here we can test once we've got our data in our notebook.

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Hey does this line out with Kaggle.

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So that's what we'll have to look at now.

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So how do we unzip this in Google Drive and maybe a way we can do it from here.

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Well we're going to see how to do it with code.

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So let's go unzip and now remember these cells here.

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Just like in Jupiter if we want to run something that's like on the command line we can use the bank

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symbol here or the exclamation mark.

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So this is going to go unzip and then we give it a file.

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We need the file path here.

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I believe he might be had to go coffeepot oh wait you can.

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That's going to save us some time.

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Beautiful.

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We could do that or we could just type it out for practice.

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So you actually don't need content little tidbit there so we can go here.

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Let's see how we top it out.

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Drive because we're gonna drive here.

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Drive my drive.

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Don't forget the space my drive.

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Yours might be named a little bit different to mine but this is just what mine looks like.

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Our target file is there.

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So your target file be the same as mine.

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My drive.

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And then the project folder is dog vision.

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So we need to go dog vision dog space vision and then dog breed identification dog zip.

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Is that smell right.

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I believe so.

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And then we're going to posit the D tag the destination and then we want to put it in drive just the

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exact same forward I drive my drive dog vision we just want to unzip it where it leaves I believe that

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should be enough

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wonderful.

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Let's run this so we can shift it into what we could do that little play button.

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This little play button here and now we're gonna get a big output of messages here because it has to

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go through and unzip 10000 files into dog vision.

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Now it may take a little while for this folder to update over here but we can be sure that it's running

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by having a look at all this.

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So say these are all test images.

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Now again this might take a little while.

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So while this code is running I'm going to stop this video here and we'll come back in the next one.

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Once we've unzipped all of our data in the dog vision file and then we'll have our data ready to be

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used for our project.

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There we go.

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We've got some updates.

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So this might take a few minutes to run.

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Make sure it's fully run before we go into the next segment because otherwise if it's not fully run

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you'll come into the same mistake I made when trying to work with your data before it had been unzipped.

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And so you end up working with less files than what Kaggle says there is and that causes whole bunches

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of errors down the track.

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So we'll let this run it may take a few minutes but I'll see in the next video once this is completed

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and we'll go through what it's unzipped.