In the prior series, Low-Code Machine Learning with Azure ML, we saw how to get started with Azure Machine Learning in a fairly pain-free way, especially for developers getting started with machine learning. In this series, I will assume that you already know all of those details and instead, we’re going to go full-code.
There are a few different ways in which we can go full-code with Azure ML. Today, we’re going to look at the easiest of those methods: using Jupyter notebooks within Azure ML Studio.
Read on for the first post in the series.