The Statistical Computing and Data Visualisation Section is now offering tutorials.
Deploying your model code into production with Microsoft Azure
Objectives:
To educate attendees on processes and tools to deploy local python or R modelling code into high-quality, robust, scalable production code.
To provide attendees with a practical overview of Microsoft Azure Machine Learning Studio
Target Audience:
Data Science practitioners who write python or R code to build predictive models, and are interested in industry best practice for converting experimental code into reliable ML services for their users.
Agenda and Schedule:
Welcome and Introduction
1 hour – Session 1: Intro to Azure Machine Learning Studio
15 min – Break
1 hour – Session 2: Model Training and Inference
15 min – Break
45 min – Session 3: Deployment and Monitoring
15 min – Conclusion and Next Steps
Facilitators and Speakers:
Dean Marchiori
Dean Marchiori is Director and Principal Data Scientist at Wave Data Labs where he consults on statistical modelling, applied mathematics and advanced analytics. Dean holds a BSc. in Mathematics with University Medal from Charles Sturt University, a Master of Applied Finance degree, and a Master of Applied Statistics from Macquarie University where he was awarded the Julian Leslie Prize in Statistics. He has been named one of the top 10 analytics leaders in Australia by the Institute of Analytics Professionals of Australia (IAPA). He is also recognised as an Accredited Statistician with the Statistical Society of Australia where he is co-chair of the committee for Statistical Computing and Visualisation.
Materials and Handouts:
Active participation will require users to sign up for an account with Microsoft Azure. This is a paid services, but Microsoft offers new users with a $200 USD credit to use within 30 days.
https://azure.microsoft.com/en-au/free
Cancellation Policy
Occasionally courses have to be cancelled due to a lack of subscription. Early registration ensures that this will not happen.
Cancellations received prior to two weeks before the event will be refunded, minus a $25 administration fee. From then onward no part of the registration fee will be refunded. However, registrations are transferable within the same organisation. Please advise any changes to events@statsoc.org.au.
For any questions, please email events@statsoc.org.au
@StatSocAus
