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Before you begin
- Labs create a Google Cloud project and resources for a fixed time
- Labs have a time limit and no pause feature. If you end the lab, you'll have to restart from the beginning.
- On the top left of your screen, click Start lab to begin
Create a Cloud Storage Bucket
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Train the Model on Vertex AI
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Copy the Batch Prediction Results
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In other labs the Fashion MNIST dataset is used to train an image classifier. In this case you had images that were 28x28 where the subject was centered. In this lab you'll take this to the next level, training to recognize features in an image where the subject can be anywhere in the image!
You'll do this by building a horses-or-humans classifier that will tell you if a given image contains a horse or a human, where the network is trained to recognize features that determine which is which.
In this lab, you will learn how to:
Although this is a self-standing lab, to maximize your learning, consider taking the lab, Classify Images with TensorFlow Convolutional Neural Networks.
Read these instructions. Labs are timed and you cannot pause them. The timer, which starts when you click Start Lab, shows how long Google Cloud resources will be made available to you.
This hands-on lab lets you do the lab activities yourself in a real cloud environment, not in a simulation or demo environment. It does so by giving you new, temporary credentials that you use to sign in and access Google Cloud for the duration of the lab.
To complete this lab, you need:
Click the Start Lab button. If you need to pay for the lab, a pop-up opens for you to select your payment method. On the left is the Lab Details panel with the following:
Click Open Google Cloud console (or right-click and select Open Link in Incognito Window if you are running the Chrome browser).
The lab spins up resources, and then opens another tab that shows the Sign in page.
Tip: Arrange the tabs in separate windows, side-by-side.
If necessary, copy the Username below and paste it into the Sign in dialog.
You can also find the Username in the Lab Details panel.
Click Next.
Copy the Password below and paste it into the Welcome dialog.
You can also find the Password in the Lab Details panel.
Click Next.
Click through the subsequent pages:
After a few moments, the Google Cloud console opens in this tab.
Cloud Shell is a virtual machine that is loaded with development tools. It offers a persistent 5GB home directory and runs on the Google Cloud. Cloud Shell provides command-line access to your Google Cloud resources.
When you are connected, you are already authenticated, and the project is set to your Project_ID,
gcloud
is the command-line tool for Google Cloud. It comes pre-installed on Cloud Shell and supports tab-completion.
Output:
Output:
gcloud
, in Google Cloud, refer to the gcloud CLI overview guide.
In the Google Cloud console, on the Navigation menu (), click Vertex AI > Workbench.
Find the
The JupyterLab interface for your Workbench instance opens in a new browser tab.
Read the narrative and make sure you understand what's happening in each cell.
In order to view the status of training and deployment on Vertex AI, you can follow the instructions in the notebook containing illustrations.
REGION
that has been assigned to you in the student resource panel.Click Check my progress to verify whether the bucket is created.
Click Check my progress to verify the objective.
Click Check my progress to verify the objective.
In this lab, you used convolution to identify features in an image where the subject could be anywhere in the image!
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Manual Last Updated December 12, 2024
Lab Last Tested December 12, 2024
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