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
- A laptop
- A free Azure subscription
- Visual Studio Code
- .NET Core SDK
YOU MAY ALSO LIKE:
- Lightning Talk: Deep Learning in .NET - It's Here! (SkillsCast recorded in September 2019)
- Functional Concurrency in .NET with C# and F# with Riccardo Terrell (Online Course on 8th - 11th March 2021)
- NodeJS, ML, K8s and Unethical Face Recognition (SkillsCast recorded in December 2020)
- Machine Learning Made Easy with ML.NET and F# (SkillsCast recorded in October 2020)
Tutorial: Real-Time Stream Analytics <3 Machine Learning
Alexander Slotte
Originally from Sweden, Alexander has 10+ years of professional software development experience, solving problems for a wide range of industries.