Talk Abstract: MLOps: are we there yet?
Situated at the intersection of R&D and IT operations,
MLOps is crucial to realising the potential of Data Science: after
all, what good is a model that’s superbly accurate but never used? Why
capture exquisitely complex relationships automatically yet require
constant human supervision and intervention? During this talk, we will examine some common hurdles to operationalisation across the entire Data Science lifecycle, from data engineering and modelling through to deployment and monitoring. We
will highlight similarities and differences with traditional DevOps
best practices and discuss their applicability in Data Science. We
will also discuss some implementation details using both open-source
and commercial solutions.
Bio: Gianluca Campanella is a Data Scientist at Microsoft and leads
the Data Science consulting and training company Estimand. He has
trained hundreds of professionals and spoken at many industry
conferences and events. Gianluca’s background is in Mathematics and Computer Science. He holds a PhD in Biostatistics from Imperial College London, an MSc in Applied Mathematics from Universidade NOVA de Lisboa, and a BSc in Computer
Science from the Free University of Bozen-Bolzano.