SQLBits encompasses everything from in-depth technical immersions to the enhancement of valuable soft skills. The full agenda will be announced in the spring; in the meantime check out the timetable and content we cover below.
2024 Training Days
Presenting 2024’s selection of training days, encompassing a deep dive into a range of subjects with some of the best data trainers in the world.
- 08:00 Registration opens and breakfast served.
- All training days run simultaneously across the venue from 09:00 – 17:00 with co-ordinated breaks.
- All training days include regular refreshment breaks and a lunch stop to rest, recharge, and chat to fellow delegates.
- No evening events planned, but if you’re staying over the night beforehand, why not join us in the Aviator on Monday night to meet the training day speakers for an informal drinks reception.
Machine Learning In Production: Azure, Docker, Kubernetes
Description
Pick up a book on Machine learning and it will explain the process for machine learning, many citing CRISP-DM as the ideal process. CRISP-DM is an iterative approach to Data Mining. It starts with business understanding the flows to data understanding, data preparation, modelling, evaluation, then either loops back around or your model is deployed. How it is deployed, well no one ever tells you that! It is this problem this course solves. If you look at the image to the right you will see the vast array of options available. With each comes more complexity and sophistication.
In this session we will build a basic model and promote them into production, using a variety of techniques in Azure. The biggest problem a lot of customers face is not how to build a machine learning model, but it which technology they should use. This question depends on so much and as a result there are multiple options in Azure. This session will demonstrate the various options for deploying a model. We will end the day with an example which will allow you to deploy and model, in any language using Docker, Python and Kubernetes.
Learning Objectives
Previous Experience
Tech Covered
Deploying, Cloud, Kubernetes, Python, Docker, AI and data science, Developing, Managing