Low-Code ML with Azure ML


If you want to build a machine learning model but don't know where to begin, this talk is for you. In this talk, we will take a look at Azure Machine Learning. We will gain an understanding of how to create an Azure ML workspace and step through the process of training, testing, and deploying a model, starting from data importation and ending when we have built a model which our applications can access. We will focus on Azure ML's Automated Machine Learning capabilities, which uses your data and a few key decisions to build out a model in just a few clicks. After that, we will look at the Azure ML designer, which provides a drag-and-drop interface for model development. This talk assumes no familiarity with Azure Machine Learning or languages like R or Python.


I have created a playlist for Azure Machine Learning YouTube videos. These include most of the content of this talk series, as well as some additional notes.