ProgNET London 2019
We know how it goes. You go to a conference, listen to awesome talks and leave full of ideas you can’t wait to implement. The next week you’re back at your desk and the finer details are slipping away...ProgNET London does things differently.
With one day of talks followed by two days of practical hands-on workshops, ProgNET London has you put down those ‘lecture notes’ and start deploying your new skills straight away. Here, you’ll be writing your own code under the guidance of leading experts. So there’s no need to worry about those after-party beers wiping away your new-found .NET knowledge!
.NET is constantly evolving. Sharpen your skills and stay in-the-know with ProgNET London: the three day conference covering the most important .NET developments.
10 South Place, London, EC2M 7EB, GB
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 session you will cut through all the foreign jargon and explore Azure Stream Analytics and the open-source cross-platform library ML.NET. By the end, you will have discovered how to: - Utilize ML.NET to train your own custom machine learning model - Deploy your custom machine learning model to an Azure Function - Setup a real-time data pipeline with Azure Stream Analytics - Learn how to write ASQL and utilize temporal windows - Integrate your machine learning endpoint in your real-time data pipeline to derive actionable insight on the fly - Learn and get experience with various Azure Stream Analytics ingress and egress features