This guide walks you through the steps to create a new notebook in Azure AI ml. Notebooks are interactive development environments that allow you to write and execute code, visualize data, and explore your machine learning models. They are a key component of the Azure AI ml development workflow.
Select an appropriate Azure region for your AI ml workspace. This will impact latency and cost. Consider proximity to your data and users.
Create a compute instance. This is where your notebook will run.
Once the compute instance is running, launch a notebook. You can do this from the AI ml workspace. Choose a framework (e.g., Python, R) and start building your machine learning solutions.
Now that you've created a notebook, you can start experimenting with machine learning algorithms, training models, and deploying them to production. Refer to the Azure AI ml Getting Started guide for more information.