‫Wonderful.
‫So that took about 5 minutes on my machine.
‫Now, again, this will really depend how long, how many files there are far out, close to 10,000
‫images in the test file and over 10,000 images in the training file.
‫But if we have a look here, we started with this zip file, then we ran this command to unzip it.
‫And now we've got sample submission, CSV, label, CSV, train and test.
‫And if we come back to our local machine, we can see we've got the same folders here.
‫So it's as if we've just unzip the file on our local machine.
‫But we've done it in Google Drive and now we can access these files in co lab.
‫If we come back to Kaggle, we've got the exact same data sources here.
‫Now again, you could have done this with the Kaggle API, but I'm just showing you if what if you didn't
‫have a dataset that was on Kaggle.
‫This is just one way to get data into your Google CoLab notebook from Google Drive.
‫And if we come back over into our Google Drive, we go back to dog vision, have a look at the test
‫folder.
‫We can see what some of the images look like.
‫But again, we're not really worried about looking at them in Google Drive.
‫We're more worried about looking at them in Google CoLab.
‫We've gone through the steps that we needed to in our setting up our project folder.
‫So getting our data ready, let's see how we can interact with code.
‫So now that our data is in our CoLab notebook, let's finish setting it up and getting it ready for
‫this project.