Terry McCann
Microsoft MVP. Principal consultant & Owner of Advancing Analytics. A consultancy who help businesses advance their analytics and better understand their data. Frequent speaker at events across the globe. Organiser of the Data Science user group in Exeter, UK and previous co-organiser of SQL Saturday Exeter, UK.
Terry McCann's Training Days
Get there faster with Machine Learning in Azure SynapseSQLBits 2022
Looking to understand Machine Learning in Azure Synapse, then look no further.
Machine Learning In Production: Azure, Docker, KubernetesSQLBits 2020
Productionisation of Machine Learning models is the hardest problem in Data Science! In this session we fix that using Docker, Kubernetes and Python.
Azure Databricks: Engineering Vs Data ScienceSQLBits 2019
Azure DataBricks can be used for both engineering and for data science. This session is led by two Microsoft MVPs, facing off. Engineer vs Scientist. The session is half how to build data pipelines and half how to do machine learning at scale.
A Data Engineer’s Guide to Azure SQL Data WarehouseSQLBits 2018
Azure SQL Data Warehouse provides a blazing fast, petabyte-scale SQL system. This all-day pre-con helps you, the data engineer, make the most of all this power by learning directly from the Microsoft Product group and industry leading consultants.
Terry McCann's Sessions
Docker & Kubernetes for the Data ScientistSQLBits 2022
Deployment == Return on investment. This session looks to show you how to do that for Machine Learning.
Machine Learning in Azure SynapseSQLBits 2022
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 CanvasSQLBits 2020
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 DatabricksSQLBits 2020
In this session we focus on how Spark implements Machine Learning at Scale with Spark ML.
Using AI to write session submission to SQLBits.SQLBits 2019
Deep Neural Networks, Long Short Term Memory Models, Data Science, AI, Fun for all the family. Using SQLBits data to write new sessions. Deep technincal but light and fun.
Deploy ML models faster with Data Science DevOpsSQLBits 2019
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 2017SQLBits 2018
This session explores SQL Server 2017's Graph processing to better understand interconnectivity and behaviour in your data.
Docker & Kubernetes for the Data ScientistSQLBits 2022
Deployment == Return on investment. This session looks to show you how to do that for Machine Learning.
Machine Learning in Azure SynapseSQLBits 2022
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 CanvasSQLBits 2020
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 DatabricksSQLBits 2020
In this session we focus on how Spark implements Machine Learning at Scale with Spark ML.
Deploy ML models faster with Data Science DevOpsSQLBits 2019
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 2017SQLBits 2018
This session explores SQL Server 2017's Graph processing to better understand interconnectivity and behaviour in your data.