In this lab, you explore the use of the What-If Tool (WIT) for image recognition models. Your task is to predict whether a person is smiling. The lab provides a CNN (Convolutional Neural Network) that is trained on a subset of CelebA dataset and visualizes the results on a separate test subset.

Objectives

In this lab, you will perform the following tasks:

• Launch an AI Platform Notebook.
• Download the pre-trained Keras model.
• Define helper functions for dataset conversion from csv to tf.
• Load the csv file into pandas dataframe and process it for WIT.
• Load the Keras models.
• Define the custom predict function for WIT.

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/LmJmoKSdFBu7tnPtVEuWoJY0qOf3zuTBVo6QE%2FEdMDw%3D

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

4. In the Customize instance menu, select the version of TensorFlow Enterprise 2.1 Without GPUs.

https://cdn.qwiklabs.com/je1UHYm5RXef3UYBs5M1ma4LkGlY8orA6TGpZk1uoGg%3D

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.

After a few minutes, the AI Platform console will display your instance name, followed by Open JupyterLab.

6. Click Open JupyterLab.

Clone the sample code