As data scientists we are great at machine learning, statistical modelling, visualising data and using data to tell a story. What are we not so good at? A lot of the core skills required in traditional software development. If you answer no to any of the following you need to attend this session. Do you source control your models? Do you test your models? Is the percentage of models deployed in production less than 10 per cent? 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.
Required audience experience
Background in machine learning
Objective of the talk
To show data scientists some of the core aspects of good code development that they can apply to their own models to allow them to get models deployed quicker.
You can view Terry’s presentation below: