Production ML: 6 Key Challenges & Insights—an MLOps Roundtable Discussion

January 24, 2024

Navigating the journey from a promising ML concept to a robust, production-ready application is filled with challenges. Teams need to establish efficient data pipelines, understand and attribute their costs, and design organizational processes that …

Navigating the MLOps Landscape: 4 Key Insights From apply(ops)

December 19, 2023

Check out this blog post for the 4 major takeaways from apply(ops), which featured talks from Uber, HelloFresh, Riot Games, and more.

How Plaid Uses Tecton to Detect and Prevent Fraud

November 9, 2023

Learn how Plaid built Signal, an ML platform that powers payment fraud detection and prevention, in this post.

Machine Learning for Risk & Fraud Detection: 4 Key Insights From apply(risk)

July 28, 2023

apply(risk), the biggest online conference for fraud detection in the ML community, featured many informative talks. Check out this post for four major takeaways from the event.

The State of Applied Machine Learning 2023

July 20, 2023

Ever wonder what the most common use cases are for applied ML? Or how fast companies are adopting MLOps solutions? Or what the main challenges are when adopting applied ML? Over 1,700 ML practitioners—from data science to ML and data …