SQLBits 2022

Machine Learning in Azure Synapse

There is a lot of content available on Synapse for Data Engineering, but what about Machine Learning? In this session we will look at how to integrate a SparkML model in Synapse.

There is a lot of content available on Synapse for Data Engineering, but what about Machine Learning? In this session we will look at how to integrate a SparkML model in Synapse.

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Terry McCann's previous sessions

Docker & Kubernetes for the Data Scientist

Deployment == Return on investment. This session looks to show you how to do that for Machine Learning.

Machine Learning in Azure Synapse

There is a lot of content available on Synapse for Data Engineering, but what about Machine Learning? In this session we will look at how to integrate a SparkML model in Synapse.

Rapid Requirements: Introducing the Machine Learning Canvas

In this session, we will introduce the Advancing Analytics Machine Learning Canvas and how it can be used to capture requirements for Machine Learning Projects.

Machine Learning in Azure Databricks

In this session we focus on how Spark implements Machine Learning at Scale with Spark ML.

Deploy ML models faster with Data Science DevOps

In this session I will show you how to apply DevOps practices to speed up your development cycle and ensure that you have robust deployable models. We will focus on the Azure cloud platform in particular, however this is applicable to other platforms

Enhancing relational models with graph in SQL Server 2017

This session explores SQL Server 2017's Graph processing to better understand interconnectivity and behaviour in your data.