[Article] Data Drifting in AutoML

[igoralcantara]

Good day Qlik Community!

Some of you probably noticed a couple months ago that AutoML now has Data Drift Monitoring capabilities. This is huge! It adds a lot of power to the MLOps cababilities of AutoML. But, what is Data Drifting really? Why is so important? How does AutoML calculates this? What is the impact?

To answer those and more questions, I wrote an article at Data Voyagers about this very topic, my 4th on the topic of the theories behind AutoML.

You can read it here:

Data Drift Monitoring and the Health of Machine Learning Models

[Camilla84]

Great article! Data drift monitoring is crucial for maintaining model accuracy over time. AutoML’s new capabilities make MLOps even more powerful!

[marksouzacosta]

Thanks for sharing Igor.

[SergioProba]

Great article! Love how you explained data drift with such fun 90s references. Automating drift detection is a game-changer for MLOps. Keep the insights coming!

[hugo_andrade]

Thanks for sharing the article. Great content! This is a must read on the topic!