The observability blog

Learn how model observability can help you stay on top of ML in the wild and bring value to your business.

November 5th, 2020

Part II: Safely rolling out models to production

This piece is the second part of a series of articles on production pitfalls and how to rise to the challenge.  – In the first part of this article, we looked at the reasons that make “the ML Orchestra” such a complex one to tune, and laid out the best practices and processes to be...
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October 29th, 2020

Part I: Safely rolling out ML models to production

This piece is the first part of a series of articles on production pitfalls and how to rise to the challenge.  – Best CICD practices for the painless deployment of machine learning models and versions For any data scientist, the day you roll out your model’s new version to production is a day of mixed...
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October 11th, 2020

AI for marketing: how well is it working for you?

While it is true to say that AI is everywhere, this is especially accurate when it comes to 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 the lifetime...
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September 22nd, 2020

How efficient are your fraud & data science teams?

Have you ever tried to find a needle in the haystack? That’s what fraud prevention feels like for most, and this is why fraud detection vendors leveraging machine learning have been burgeoning these past years. After all, it is, to date, the best way to identify issues in the millions of transactions that go through...
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