• How to train your model locally
• How to train your model remotely using Azure ML compute
• E2E MLOps pipeline

• VsCode
• Python 3.7
• A virtual environment tool (venv)
• An Azure account
• An Azure ML workspace

• Install Visual Studio Code

• Install Python 3.7

• Installation To install virtualenv via pip run: $ pip3 install virtualenv

• Creation of virtualenv:

  • Windows $ python -m virtualenv venv (in the openAI workshop directory)
  • Mac $ virtualenv -p python3

  Activate the virtualenv: $ source /bin/activate

  Deactivate the virtualenv: $ deactivate

• Installation To install virtualenv via pip run: $ pip3 install virtualenv
• Creation of virtualenv:
  • Windows $ python -m virtualenv venv (in the openAI workshop directory)
  • Mac $ virtualenv -p python3

• Activate the environment Windows: .\venv\Scripts\activate.ps1 Mac: $ source ./venv/bin/activate

• Make sure you have the requirements installed in your Python environment using pip install -r requirements.txt.

• Rename the '.env.template' file to '.env' and modify as follows:

SUBSCRIPTION_ID = "<azure subscription id here>"
RESOURCE_GROUP = "<resource group>"
AML_WORKSPACE_NAME = "<azure ml worskpace name>"

Save the .env file