6.3. ML model monitoring dashboard with Evidently. Online architecture [CODE PRACTICE]

A code example walkthrough of creating a live ML monitoring dashboard for online architecture using Evidently.

Video 3. ML model monitoring dashboard with Evidently. Online architecture [CODE PRACTICE]arrow-up-right, by Emeli Dral

In this video, we create a live ML monitoring dashboard for an ML model deployed as a service. We imitate sending the live data directly from the machine learning service to the ML monitoring service and update the dashboard in near real-time.

Want to go straight to code? Here is the code examplearrow-up-right to follow along.

Outline: 00:00arrow-up-right Introduction 00:30arrow-up-right Script overview and imports 01:59arrow-up-right Define Collector, Workspace, and Project variables 03:31arrow-up-right Load data and create mini-batches to simulate production usage 04:39arrow-up-right Implement the function to generate Test Suites 06:38arrow-up-right Create the Workspace, Project and add Dashboard panels 09:25arrow-up-right Set up and configure the Collector service 13:00arrow-up-right Simulate sending data to the Collector 15:48arrow-up-right Implement the main function, run and debug the script 18:32arrow-up-right Run the Collector and view the online Dashboard updates 20:46arrow-up-right Recap and next steps

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