MLflow Crash Course - Model Registry and Model Deployment

[@curdyco]

where did your terminal came from? is it in your laptop? or is it in dagshub? do i pull the repo in my pc and then run the terminal?

[@curdyco]

you are using dvc command why? is there any detailed tutorial for that?

[@curdyco]

In the conda env why you only used mlflowm pillow and tf, is the because register_pyfunc were using them, but register_pyfunc was also using io, and base64?

[@DagsHub]

io, and base64 are system packages that come with python, so you don't need to mention them

[@curdyco]

@@DagsHub okay, and in conda env we add only libraries that we are using in register_pyfunc?

[@curdyco]

you are building mlflow model build-docker to create container but where is the rest api code? how can i customise the interface for user?

[@DagsHub]

Can you clarify what you mean? I'm not sure I understand the question

[@curdyco]

@@DagsHub see you said we can build a docker container using the command i mentioned above, but that docker container will not have app.py, only the model is inside the container, what about the web interface like with flask or something? what about dockerfile?