Struggling to keep your production ML models accurate without an endless budget? You’re not alone. Join us tomorrow – December 17, 9AM PT | 12 PM ET – at this virtual session featuring Tecton CTO and co-founder Kevin Stumpf and Decoding ML founder Paul Iusztin as they share practical strategies for tackling
Here’s what you’ll learn:
Key reasons why models degrade silently in production.
Why success in training doesn’t always translate to real-world performance.
Smart strategies to meet accuracy goals without overspending.
The role of feature engineering in maintaining production accuracy.
With insights drawn from their experience working with teams at Uber, Continental, and others, Kevin and Paul will dive into real-world problems and solutions. If your ML team is navigating accuracy issues, this is the session to watch.
Is there a recording?