Managing your the ML Lifecycle is one of the big problems for institutions and companies nowadays. How to shift away from the experimental notebooks and data labs and at the same time maintain the reproducability of the transparancy of the ML systems With this talk Laurens will walk you through an example of how to manage your ML system while switching around with the models and the dataset to train on. The tools used in this little demo will be MLflow and DVC and of course written in Python.
About Laurens Weijs
My name is Laurens Weijs and am currently working at the Rijks ICT Gilde as a Data Engineer. Since I started doing data science and working I have been coding within Python and still love it to this day. My interests as a data engineer is not merely coding data pipelines but especially supporting data scientists practicing MLOps. I simply love it when stuff can be automated and therefore manual boring stuff can be solved by the machines that can do it way more efficiently./i
