arted with MLOps and Github Actions to package a container with an ONNX model that does live inferencing with a Flask application. By using Azure ML, learn how to download the large ONNX model into the Github Action workflow, package it as a container and then push it to a container registry. For reference use the

Topics include:
* Create a container that does live inferencing with Flask and the ONNX runtime
* Package the model and verify it works locally
* Setup a Github Action to authenticate to Azure ML and download a previously registered model
* Build the new container as a Github Action, authenticate to Docker Hub or Github Packages
* Push the new container to the Github registry or any other registry like Docker Hub

Citación :

https://rapidgator.net/file/18dd51dd48d2941f2c70a718e1a4a2d6/sg1gb.MLOps.workflow.with.Github.Actions.Video.rar.html


https://nitroflare.com/view/957E989C0771BC6/sg1gb.MLOps.workflow.with.Github.Actions.Video.rar


https://uploadgig.com/file/download/2492D421D5932eD5/sg1gb.MLOps.workflow.with.Github.Actions.Video.rar