MLOps: bringing order to chaos
DevOps
• November 2020
MLOps: bringing order to chaos
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About
MLOps: bringing order to chaos
About
ML development exposes a lot of challenges to organisations. Unlike traditional developers, ML engineers focus more on experimentation, often tweaking and retraining their modules as the flow to production is less linear, requiring more complex feedback.
With MLOps the classical DevOps principles are applied to machine learning operations, with the introduction of new roles, new components and processes. A MLOps framework allows a complete machine learning model lifecycle management, from development to deployment, with a continuous monitoring that reduces complexity and risk of failure.
Language
Italian
Level
Intermediate
Length
41 minutes
Type
online conference
About the speakers
About the speakers
Virginia Becchetti
Data Scientist •
NTT DATA
I graduated in Statistics and during the degree i got passionate about Data Science.
I like to design innovative technological solutions because I believe it is essential to try to keep up with the evolution of the IT landscape. Now i'm working as a Data Scientist and i manage the development of different ML solutions in all phases of their life-cycle, from the design, to development and production. In the last year i have been strongly passionate about the MLOps discipline, fundamental for anyone who is developing ML solution and for companies that decide to approach ML world.
Luca Corsini
DevOps Engineer •
NTTData Italia
DevOps Engineer for NTT Data Italia, technology enthusiast, Linux sysadmin at heart, rock climber, cat lover, gunpla builder.
Details
Language
Italian
Level
Intermediate
Length
41 minutes
Type
online conference
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