Welcome to "NLP on Azure – Hands-on Labs for MLOps"

Overview

This repository contains content of a four part workshop of using Tensorflow 2.0 on Azure Machine Learning service. The different components of the workshop are as follows:

• Part 1: Preparing Data and Model Training
• Part 2: Inferencing and Deploying a Model
• Part 3: Setting Up a Pipeline Using MLOps
• Part 4: Explaining Your Model Predictions

The workshop demonstrates end-to-end Machine Learning workflow on the example of training a BERT model to automatically tag questions on Stack Overflow.

Getting started with the workshop environment

1. Login to Azure ML studio

   • Once the workshop enviroment is ready, you can open new browser tab and navigate to Azure ML studio, using it's direct URL: https://ml.azure.com. We recommend to use Private Browser window for the login to avoid conflicting credentials if you already have Azure subscription.
   • Use credentials provided in the workshop environment to sign-in to Azure ML studio.
   • In the Welcome screen select preprovisioned subcription and workspace similar to screenshot below:
   • Click Get started!
   • In the welcome screen click on Take a quick tour button to familiarize yourself with Azure ML studio.

2. Create Azure Machine Learning Compute Instance VM

   • Click on Compute tab on the left navigation bar.
   • In the Compute Instance section, click New.
   • Enter Compute Instance name of your choice and click Create. Creation should take approximately 5 minutes.

   

3. Clone this repository to Compute Instance in your Azure ML workspace

   • Once Compute Instance is created and in Running state, click on the Jupyter link. This will open Jupyter web UI in new browser tab.
   • In Jupyter UI click New > Terminal
   • Notice the name of your user folder and run following command
   • Clone the repository of this workshop by executing following command:

   git clone [yourRepoURI]

   

   • If you need password to clone repo, go to repo in ADO; click 'Genterate Git Creadentials'; copy the password;

   

4. Open Part 1 of the workshop

   • Go back to the Jupyter window.
   • Navigate to bert-stack-overflow/1-Training/ folder.
   • Open AzureServiceClassifier_Training.ipynb notebook.

   

You are ready to start your workshop! Have fun.