Performance of sub-groups
March 4th, 2021

Models don’t perform identically on different sub-groups of input data. So how should you go about measuring the performance of sub-groups? Let’s dive in and see how.

Measuring the performance of sub-groups
Get your business closer to your models
November 26th, 2020

So how do you go about aligning business and ML to make sure your AI program is not at risk?

Aligning business and ML
Part I: Safely rolling out ML models to production
October 29th, 2020

This piece is the first part of a series of articles on production pitfalls and how to rise to the challenge.  – CI/CD best practices to painlessly deploy ML models and versions For any data scientist, the day you roll out your model’s new version to production is a day of mixed feelings. On the

Part I: Safely rolling out ML models to production
AI for marketing
October 11th, 2020

While it is true to say that AI is everywhere, this is especially accurate when it comes to AI for marketing. Every leading marketing team today knows that machine learning can dramatically help them boost their effectiveness and their impact. Whether it’s to identify and engage users who are most likely to convert, ensure that

AI for marketing: how well is it working for you?
How efficient are your fraud & data science teams
September 22nd, 2020

In this blog, we look at how fraud detection solution vendors can leverage their ML monitoring solutions to boost the efficiency of their fraud and data science teams and deliver better service to their merchants.

Fraud detection in machine learning