In my last post I had written about deploying models on AWS. So, I though it would only be fitting to write one for GCP, for all the GCP lovers out there.
GCP has a service called the AI Platform which, as the name suggest, is responsible for training and hosting ML/AI models.
Just like the last post, this post, through a PoC, describes -
How to add a trained model to a Google Cloud bucket Host the saved model on the AI Platform Create a Service Account to use the model hosted on AI Platform externally Make a Streamlit app to make a UI to access the hosted model All the code can be found in my Github repository.
Quite a while back, I had written a post in which I described how to package your Machine Learning models using Docker and deploy them using Flask.
This post, through a PoC, describes -
How to package your model using Docker (similar as last post) How to push the Docker container to Amazon ECR Add a Lambda Function for your model Make a REST API using Amazon API Gateway to access your model Automate the whole process using Github Actions, so that any updates to the model can take effect immediately Make a Streamlit app to make a UI to access the REST API (for the model deployed on AWS) All the code can be found in my Github repository.