hanes_egi (hanes_egi)

2023: Machie Learning Modelling and Deployment

Prepare prediction model in "h.5" format, file are stored in "ML-Backend" folder
Write main.py base on machine learning testing model, files are saved in the "ML-Backend" folder
Create file named "requirement.txt" for library you need for running our code
Create file named "Dockerfile" for run system in our container
Create file named ".dockerignore" for ignore system to ignore spesific file.
Create folder static/uploads to save photos for prediction progress.
Create new Project in Google Cloud Platform
Active Cloud Run API and Cloud Build API
Install and init Google Cloud SDK (Use this link : https://cloud.google.com/sdk/docs/install)
Use Cloud Build to import our code to our cloud services ( gcloud builds submit --tag gcr.io/<project_id>/<function_name>)
Use Cloud Run to deploy our API ( gcloud run deploy --image gcr.io/<project_id>/<function_name> --platform managed )