Welcome to "Azure ML Training" Workshop!

Overview

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

• Part 1: Model Training
• Part 2: Inferencing and Deploying a Model

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

   • Navigate to: https://ml.azure.com.
   • In the Welcome screen select preprovisioned subcription "AzureML Nursery" and workspace "mltraining-westeurope-N-ws". Select N based on the workspace assigned to you:

2. Create Azure Machine Learning Notebook VM

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

3. Clone this repository to Notebook VM in your Azure ML workspace

   • Once Notebook VM is created and is in Running state, click on the Jupyter link. This will open Jupyter web UI in new browser tab.
   • In Jupyter UI click New > Terminal.
   • In terminal window, type and execute command: ls
   • Notice the name of your user folder and use that name to execute next command: cd <userfolder>
   • Clone the repository of this workshop by executing following command: git clone https://github.com/maxluk/bert-azureml-training.git

4. Open Part 1 of the workshop

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

You are ready to start training your model! Have fun.