Low-Code ML with Azure ML

ABSTRACT

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.

ADDITIONAL MEDIA

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.

SLIDES

Click here to access the slides for this presentation.

The slides are licensed under Creative Commons Attribution-ShareAlike.

DEMO CODE

Click here to access demo code for this presentation.

The source code is licensed under the terms offered by the GPL.