[Day 164] Learning about model deployment (and deleting AWS services)
Hello :) Today is Day 164! A quick summary of today: started Module 4: deployment from the MLOps zoomcamp re-creating a baseline OD demand matrix model - ConvLSTM Firstly, about module 4: deployment Code from today is on my github . The first part was about simple model packaging with pickle and serving the model through a flask api Second part was about using mlflow and saving the ran experiments to S3 on AWS The code is pretty much like the one in the pic above, but with the below added above it: RUN_ID = "" AWS_S3_BUCKET = "" logged_model = f's3://{AWS_S3_BUCKET}/1/{RUN_ID}/artifacts/model' model = mlflow.pyfunc.load_model(logged_model) And this is when I realised I am getting charged by AWS. It is only $9, but I cannot continue using it. I thought I am under some 'free tier' but nope... I started deleting all EC2, RDS, Load balancers, Users, everything I could see. But because I am not completely sure, I wanted to use some cloud-nuke tool - and