Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that…

Deleting an existing Jupyter kernel is not a prerequisite for adding a new one. A compute instance in Azure Machine Learning can support multiple kernels simultaneously. The correct procedure to add a new kernel involves creating a new environment (for example, a Conda environment), activating it, installing the ipykernel package within that environment, and then using the ipykernel command to register the new environment as a kernel. Deleting the default Python 3.6 - AzureML kernel is an unnecessary and potentially disruptive action that does not facilitate the addition of a new kernel.

A. Yes: This is incorrect because deleting the default kernel is not a required step. New kernels are added alongside existing ones, and the system is designed to manage multiple kernels.

1. Microsoft Azure Documentation: Add new Jupyter kernels to a compute instance. This official guide details the process for adding a new kernel. The steps are: 1. Use the terminal to create a new environment. 2. Activate the environment. 3. Install the pip and ipykernel package into the new environment. 4. Install the new kernel. The documentation makes no mention of deleting an existing kernel as a prerequisite.

Source: Microsoft Docs

"How to create and manage an Azure Machine Learning compute instance"

Section: "Add new Jupyter kernels".

2. Microsoft Azure Documentation: Customize a compute instance with a startup script. This document shows advanced customization

including setting up environments and kernels. It demonstrates adding new kernels without removing the default ones

reinforcing that deletion is not a required step.

Source: Microsoft Docs

"Customize a compute instance with a startup script"

Section: "Example scripts".

3. Jupyter Project Documentation: Kernels for different environments. The official documentation for Jupyter (the underlying technology in Azure ML Notebooks) explains how to install kernels. The process always involves creating an environment and registering it

allowing multiple kernels to coexist.

Source: IPython/Jupyter Documentation

"Kernels for different environments"

Section: "Installing a kernel".