Open SSH Connection in VS Code to Azure Ubuntu VM to Perform Remote Development

VS Code is a useful development tool which can be used on any platform to develop code in any language of your preference. In an Azure Ubuntu VM without setting up the desktop remote access, you may want to perform development work and may want to perform debugging activities, as you are doing with local files in a Linux environment. You can use ssh extension for VS Code and create ssh connection to a VM in Azure or anywhere over ssh and work connected to the remote Linux, MacOS or Windows machines via VS Code. Let’s look at steps to connect to a Ubuntu VM on Azure using a VS Code in Windows 10 local machine.

Deploying Machine Learning (ML) Model with Azure Pipeline Using Deployable Artifact from Build

We have discussed how to create a Machine Learning (ML) model as a deployable artifact in the post “Training Machine Learning (ML) Model with Azure Pipeline and Output ML Model as Deployable Artifact” which is based on the open source ML repo, (https://github.com/SaschaDittmann/MLOps-Lab.git) with data by Sascha Dittmann, which also contains the code to train a model.

Training Machine Learning (ML) Model with Azure Pipeline and Output ML Model as Deployable Artifact

Training a machine learning model requires wide range of quality data to get the ML model trained in such a way that it can provide accurate predictions. Azure build pipeline can run the python tests written to validate the data quality and the train a model with uploaded data to Azure ML workspace. In this post on “Setup MLOPS workspace using Azure DevOps pipeline” it is clearly explained how to setup an Azure ML workspace in a new resource group dynamically with Azure CLI ML command extension. The post “Setup MLOPS workspace using Azure DevOps pipeline” as well as this post on training a model with Azure pipelines use the open source ML repo (https://github.com/SaschaDittmann/MLOps-Lab.git) with data by Sascha Dittmann, and code to train a model.