In this lab, you use the What-If Tool to identify potential biases in a model that was trained on a mortgage loan applications dataset.

Objectives

In this lab, you will perform the following tasks:

• Build a binary classification model using XGBoost.
• Deploy the model to Cloud AI Platform.
• Use the What-If Tool on the deployed model to search for biases.

Create a storage bucket

Create a bucket using the GCP Console:

1. In the Cloud Console, on the Navigation menu, click Storage.
2. Click Create bucket.
3. Choose a Regional bucket and set a unique name (use your project ID because it is unique). Then, click Create.

Start a JupyterLab Notebook instance

1. In the GCP Console, in the Search bar, type in Notebook.
2. Select Notebooks for AI Platform.

https://cdn.qwiklabs.com/8Kn7H9l27eMm%2BB6emya%2FKViTYgpJatwo1uBp6vIDUGQ%3D

3. On the Notebook instances page, click New Instance.

4. In the Customize instance menu, select the latest version of TensorFlow without GPUs.

5. In the New notebook instance dialog, for Region, select us-central1, for Zone, select a zone within the selected region, leave all other fields with their default options, and click Create.