Car Insurance Lab

This repository contains a number of labs to lilustrate the use of Google Cloud Data and AI products using a car insurance dataset

Setup

Once logged into a Google Cloud Project, open Cloud Shell and execute the following commands:

gcloud services enable bigqueryconnection.googleapis.com
gcloud services enable notebooks.googleapis.com
gcloud services enable cloudresourcemanager.googleapis.com
gcloud services enable aiplatform.googleapis.com
gcloud services enable bigquery.googleapis.com
gcloud services enable iam.googleapis.com

sleep 60


PROJECT_ID=$(gcloud config get-value project)
PROJECT_NUM=$(gcloud projects list --filter="$PROJECT_ID" --format="value(PROJECT_NUMBER)")


gcloud projects add-iam-policy-binding $PROJECT_ID \
      --member="serviceAccount:${PROJECT_NUM}-compute@developer.gserviceaccount.com"\
      --role='roles/aiplatform.serviceAgent'

gcloud projects add-iam-policy-binding $PROJECT_ID \
      --member="serviceAccount:${PROJECT_NUM}-compute@developer.gserviceaccount.com"\
      --role='roles/artifactregistry.admin'

gcloud projects add-iam-policy-binding $PROJECT_ID \
        --member="serviceAccount:${PROJECT_NUM}-compute@developer.gserviceaccount.com" \
        --role='roles/bigquery.connectionAdmin'

gcloud projects add-iam-policy-binding $PROJECT_ID \
      --member="serviceAccount:${PROJECT_NUM}-compute@developer.gserviceaccount.com"\
      --role='roles/storage.admin'

gcloud projects add-iam-policy-binding $PROJECT_ID \
      --member="serviceAccount:${PROJECT_NUM}@cloudbuild.gserviceaccount.com"\
      --role='roles/aiplatform.admin'

gcloud projects add-iam-policy-binding $PROJECT_ID \
      --member="serviceAccount:$PROJECT_NUM-compute@developer.gserviceaccount.com"\
      --role='roles/resourcemanager.projectIamAdmin'

Next, navigate to Vertex AI > Workbench and create a new notebook of INSTANCES type.

Leave all the configuration as default. Once the notebook is created, click on OPEN JUPYTERLAB to open the web interface. Click on Git > Clone a Repository and enter the following URL https://github.com/rkgogole/hdemo.

Now, edit the hdemo/src/datagen/launch_datagen.sh script and ammend the values maked with TO_DO_DEVELOPER Now, open a Terminal on the notebook and run the shell script, navigate to the datagen folder and:

source lanch_datagen.sh

This concludes the lab setup.

Interactive Labs

Now you can follow the lab instructions on the following notebooks.

You can run all of them with default Python3 kernel

• Lab #1: Smart segmentation
  • Code
• Lab #2: Hyper personalized emails
  • Code
• Lab #3: TimesFM forecasting
  • Code

Sample UI

This repository also contains sample UI, to run it perform the following steps:

1. Edit the src/ui/backend/main.py script and change the following lines:

PROJECT_ID = "TO_DO_DEVELOPER"
GCP_LOCATION = "TO_DO_DEVELOPER"
DATASET_ID = "TO_DO_DEVELOPER"

2. Execute the run_app_local.sh script located under src/ui
3. From a browser connect to https://localhost:3000