Within Azure we have a rich ecosystem of AI services that can be leveraged to gain new insights into your data. This session will give you an easy to digest breakdown of the key services that matter and how to approach each one. Cognitive Services, Bot Framework, Azure Machine Learning Studio, Databricks, Notebooks, the Azure ML SDK for Python and the Azure ML Service
We will review this new feature of ADFv2, do deep dive to understand the mentioned techniques, compare them to SSIS and/or T-SQL and learn how modelled data flow runs Scala behind the scenes.
In this session, we’ll look at the different options within the Cognitive Services suite, show you how to connect to the APIs using Python code, walk through a live bot demo, and build an Azure Cognitive Search index. You should leave this session feeling like you’ve had a jump start to further your AI developer skill set.
With a strong focus on the algorithms used in Machine Learning, we will explore the maths involved to gain a deeper understanding. Using practical examples, with Databricks to consume a dataset and Python scripts to execute the models.
Ever wondered how you can add the power of ML to your existing SQL estate without the need to invest in new services? Come to this session to learn about running Python and R workloads in SQL, the PREDICT function, and how to operationalise models in Azure SQL Database
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