Azure ML Studio – Getting to Grips with Machine Learning and Microsoft Azure
With ML Studio there is no need for a student to have any experience in computer programming so its perfect for Geography, Sociology and other discipline who create vast amounts of data.
Azure ML provides a very low-friction way of enabling students to discover how different ML algorithms perform using real-world examples, such as predicting car prices, estimating Twitter sentiment, Detecting credit risk anomalies and predicting flight delays.
Where Azure ML really helps is through instructors pre-building ML workflows and sharing them with students, either privately using a collaborative workspace, or publicly through the Azure ML gallery.
(Figure shows evaluating a model in Azure ML, including ROC curve and scoring metrics – see https://azure.microsoft.com/en-us/documentation/articles/machine-learning-walkthrough-4-train-and-evaluate-models/)
Getting Started with Azure ML
One of the best ways of getting started with Azure ML is to setup workflows with data and allow students to ‘fill-in-the-blanks’, maybe comparing how different ML algorithms perform on the same problem.
Datasets and access to data for ML
There is a plethora of sample datasets built into ML Studio for you to create educational material around, as well as many tutorials already built by the community published in the gallery.
Getting to Grips with ML
A unique feature is the ability to include your own R and Python code, so there is ultimate flexibility in what you can do. And when a model has been validated, it is easy to publish this as a web service with an auto-documented REST API, to be consumed by apps. Again all students now get Free web services with Microsoft Imagine via DreamSpark
Get started with Azure ML for education:
- There is a free tier that includes 10GB of Azure storage for our datasets, and ability to build Azure ML experiments for an hour with up to 100 modules. Get started with this here.
- Azure for Education is for Faculty running courses using Azure, including Azure ML. Each student receives $100 of Azure credit per month, for 6 months. The Faculty member receives $250 per month, for 12 months. You can apply anytime at http://www.microsoftazurepass.com/azureu
- Azure Machine Learning for Research is for University Faculty running data science courses who may need greater amounts of Azure storage and additional services such as HDInsight (Hadoop and Spark) or DocumentDB (NoSQL). Proposals are accepted every two months, you can find out more and apply at http://research.microsoft.com/en-us/projects/azure/ml.aspx
- Microsoft DreamSpark Azure offer, Web Sites, Storage, AppInsights and Visual Studio Online for FREE
Microsoft has a growing need for smart talent in this area, so we fully support the efforts of academia to educate and inspire the next-generation.
So please explore and let us know what you are doing with Azure Machine Learning and your students, we’re here to help.