ML Models To Production

ML systems are composed of independent parts of software that need to work together, hence, what are the best CI/CD practices for the deployment of machine learning models in smooth and safe way? This session will focus on how we can think about versioning, precautions that are required and how we can leverage monitoring and optimizing by using a continuous integration pipeline (CI) as well as continuous deployment (CD).
Who is this presentation for?
Data Scientists and Machine Learning Engineers / Dev Ops
Prerequisite knowledge:
Data Science pipelines
What you'll learn?
How to properly automate Data Science pipelines

Filipa Peleja is the Levi Strauss & Co Europe Lead Data Scientist at the Data Analytics & AI team. She has always been enthusiastic about technology where she first stepped into the tech world as an undergrad in Computer Science and later Ph.D. in the Machine Learning domain. Her academic accomplishments were recognized with the 1st prize of an industry challenge from a telco and publications in international conferences among which, top tier conferences like SIGIR and ACL. Before joining Levi, Filipa interned at Yahoo! Research and, later, worked as a Sr Data Scientist at Vodafone. Filipa loves to work in an area that she feels very passionate about and also enjoys passing along knowledge, hence, she lectures, supervises projects/thesis for Rumos, CodeOp, Neueda and Barcelona Technical School.