AI Project Template: `Bank Loan Classification`

Goal

This is a sample Bank Loan Classification project template where we are using a binary classification model to classify whether to grant loans to applicants or not.

Dataset

The Bank Loan Classification dataset used during the workshop is taken from Kaggle and can be found here.

Project Requirements

- Python3
- git
- Docker

Project Structure

Loan Classification Project
├── models
│   └── RF_Model_V1.pkl
├── Dockerfile
├── requirements.txt
├── deployment.yaml
├── model_api.py
└── streamlit_app.py

Accessing Deployed App

After completing the tasks your deployed model API can be accessed from the ai service endpoint in your cluster. You can also append /docs to the endpoint to have access to the Swagger UI for API Testing.

Project Steps

Step 1: Cloning the repo

git clone https://github.com/DigitalProductschool/react-spring-template.git

Step 2: Changing working directory to ai

cd react-spring-template/ai/

Step 3: Installing dependencies using pip3

pip3 install -r requirements.txt

Step 4: Running uvicorn server locally

python3 model_api.py

Note: Go to /docs route to test the api.

Step 5: Building the runner container image locally

docker build -t ai-run-image -f run.Dockerfile .

Step 6: Building the container image for our ai app using the Google Cloud Run builder locally

pack build ai:dev --env-file ./pack_envfile --builder gcr.io/buildpacks/builder:v1 --run-image ai-run-image

--env-file ./pack_envfile pass an env file to the build

--run-image ai-run-image use the custom run image called ai-run-image

Step 7: Running the container locally

docker run --rm -d -p 8000:8000 -p 8501:8501 ai:dev

Note: Visit port 8501 to access Streamlit Application and 8000/docs route to test the api.

alihussainia/ai-template