Tutorial: Real-Time Stream Analytics <3 Machine Learning

A SkillsCast for this session is not available.

It’s imperative in today’s world to be able to make split-second decisions based on real-time data. Reports based on batch data are great for looking back at trends and potentially making long-term decision, but old data is in many cases already obsolete, and the opportunity to have an actionable impact on the success of a specific process may have been lost. Furthermore, incorporating machine learning algorithms in your real-time data pipeline enables you to derive great insight on the fly and truly set your organization up for your success.

The best part, it is not as difficult as you may think!

In this workshop, you will cut through all the foreign jargon and give participants a solid machine learning and stream processing foundation.

By the end of the workshop you will be able to:

• Understand the basics of Machine Learning and Deep Learning
• Train custom machine learning models using
• ML.NET
• AutoML
• Azure Machine Learning Service
• Jupyter Notebooks with ScikitLearn/Pandas and Numpy
• Deploy your machine learning models to an Azure Function and/or Azure Container Instance
• Setup a real-time data pipeline using Azure Stream Analytics
• Understand the concept of temporal windows
• Integrate your machine learning models into your data pipeline

Prerequisites Although it is fully possible just to follow along, please make sure to have the following if you would like to participate hands-on in this tutorial

• A laptop
• A free Azure subscription
• Visual Studio Code
• .NET Core SDK

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