
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
Clone a course repo within your JupyterLab interface
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Classify text using reusable embeddings
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In this lab, you implement text models to recognize the probable source (Github, Tech-Crunch, or The New-York Times) of titles present in the title dataset, which are created in the respective labs.
In this lab, you learn how to:
For each lab, you get a new Google Cloud project and set of resources for a fixed time at no cost.
Sign in to Qwiklabs using an incognito window.
Note the lab's access time (for example, 1:15:00
), and make sure you can finish within that time.
There is no pause feature. You can restart if needed, but you have to start at the beginning.
When ready, click Start lab.
Note your lab credentials (Username and Password). You will use them to sign in to the Google Cloud Console.
Click Open Google Console.
Click Use another account and copy/paste credentials for this lab into the prompts.
If you use other credentials, you'll receive errors or incur charges.
Accept the terms and skip the recovery resource page.
AI Platform Training & Prediction API
in the search box.Navigate to Navigation menu > Cloud Storage in the Cloud console for your project, then click CREATE BUCKET.
Set a unique name (use your project ID because it is unique) and then choose region as
Confirm Enforce public access prevention on this bucket on "Public access will be prevented" pop-up.
In the Google Cloud console, from the Navigation menu (), select Vertex AI > Dashboard.
In the Navigation menu, click Workbench.
At the top of the Workbench page, ensure you are in the Instances view.
Find the cloudlearningservices instance and click on the Open JupyterLab button.
The JupyterLab interface for your Workbench instance opens in a new browser tab.
Untitled.ipynb
file in the menu bar and select Rename Notebook to give it a meaningful name.Your environment is set up. You are now ready to start working with your Vertex AI Workbench notebook.
The GitHub repo contains both the lab file and solutions files for the course.
training-data-analyst
repository.training-data-analyst
directory and ensure that you can see its contents.Click Check my progress to verify the objective.
In the Select Kernel dialog, choose TensorFlow 2-11 (Local) from the list of available kernels.
In the notebook interface, click on Edit > Clear All Outputs (click on Edit, then in the drop-down menu, select Clear All Outputs).
Carefully read through the notebook instructions and fill in lines marked with #TODO where you need to complete the code as needed
Tip: To run the current cell, click the cell and press SHIFT+ENTER. Other cell commands are listed in the notebook UI under Run.
Click Check my progress to verify the objective.
When you have completed your lab, click End Lab. Qwiklabs removes the resources you’ve used and cleans the account for you.
You will be given an opportunity to rate the lab experience. Select the applicable number of stars, type a comment, and then click Submit.
The number of stars indicates the following:
You can close the dialog box if you don't want to provide feedback.
For feedback, suggestions, or corrections, please use the Support tab.
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