Tue August 10, 2021
“Chicken or the Egg” in MLOPs: The Case of the DIY Feature Store
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While developing MLOps in an organization, one often encounters the "chicken or the egg" paradox: On one hand, a certain abstraction, workflow, or tool is hypothesized to be a good fit. On the other hand, there are often considerable integration efforts even before feasibility testing can commence.
In other words, you cannot know if the tool works unless you "buy in".
The common solution is to "build" internal implementations which optimize for integration ease. Most of these "interim" solutions take a life on their own and will only be replaced once (if) they outlive their usefulness or another abstraction is adopted.
In this webinar, we will simulate this low-integration-cost process by building a feature-rich Feature Store for offline use using the ClearML Open Architecture Stack.
show less
In other words, you cannot know if the tool works unless you "buy in".
The common solution is to "build" internal implementations which optimize for integration ease. Most of these "interim" solutions take a life on their own and will only be replaced once (if) they outlive their usefulness or another abstraction is adopted.
In this webinar, we will simulate this low-integration-cost process by building a feature-rich Feature Store for offline use using the ClearML Open Architecture Stack.
While developing MLOps in an organization, one often encounters the "chicken or the egg" paradox: On one hand, a certain abstraction, workflow, or tool is hypothesized to be a good fit. On the other hand, there are often considerable integration efforts even before feasibility testing can commence.
In other words, you cannot know if the tool works unless you "buy in".
The common solution is to "build" internal implementations which optimize for integration ease. Most of these "interim" solutions take a life on their own and will only be replaced once (if) they outlive their usefulness or another abstraction is adopted.
In this webinar, we will simulate this low-integration-cost process by building a feature-rich Feature Store for offline use using the ClearML Open Architecture Stack.
read more
In other words, you cannot know if the tool works unless you "buy in".
The common solution is to "build" internal implementations which optimize for integration ease. Most of these "interim" solutions take a life on their own and will only be replaced once (if) they outlive their usefulness or another abstraction is adopted.
In this webinar, we will simulate this low-integration-cost process by building a feature-rich Feature Store for offline use using the ClearML Open Architecture Stack.
show less
Date/Times:
Online - Virtual Event
19 Upcoming Events
., San Francisco, CA .
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