Start with Machine Learning using Azure Machine Learning (Webinar)

Start with Machine Learning using Azure Machine Learning (Webinar)
Are you interested to get started with Machine Learning but you feel your Spark or Python skills are not yet on point.

You find Databricks too complex for the models you want to build? Then Azure Machine Learning might be the ideal solution for you. 

      In this session we will:

      • Share our thoughts on when to use Azure Machine Learning
      • Share best-practices on using Pipelines, Datasets and Data Sources in Azure ML
      • Demo the non-coding ML Studio and the coding notebooks and SDK (and for example the integration with Databricks)
      • Outline how Azure Machine Learning can be used for cleaning data, building models and deploying a service

      These virtual sessions are 100% free and open for all who want to join.

      Already intrigued? Read this insight article to learn already a bit more (Microsoft changed the name, it's the same product):
      Azure Machine Learning Services: a complete toolbox for AI?

      Practicals

      This is part in a series of webinars around Azure. In these virtual, online sessions (organized via Microsoft Teams, but accessible from any browser) the element61 team will present:

      • What the solution is and the function it has in a modern data platform
      • How you can practically use it and what you need to pay attention to when setting it up
      • A real-life demo on the tool and its functionalities
      • The sessions will allow Q&A on questions from the audience

      This 1,5 hour virtual meeting will be a great way to catch-up get up to speed with the different tools. Furthermore, use the opportunity to ask your questions to our experts.
      These virtual sessions are 100% free and open for all who want to join.

      More information on the other sessions: 

      Each of the sessions can be followed as a stand-alone session.

       

      These virtual sessions are

      Date

      30 April, 2020 -
      10:30 to 12:00

      Location

      Microsoft Teams