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Model management

The third wave of operationalization is here: MLOps

Using machine learning models in products is hard. Most companies fail at extracting value from them because they can't operationalize models properly.

Verta: Model Management and Operations Platform for Production Machine Learning

Today, I’m thrilled to announce the formal launch of the Verta Model Management and Operations platform, and Verta’s $10M Series A funding led by Intel Capital. With the Verta Platform, we help data science teams to tame the chaos of brittle and fragmented…

Robust MLOps with Open-Source: ModelDB, Docker, Jenkins and Prometheus

A few weeks back, I had the pleasure of giving one of the four talks on the ML in Product Talk at the Strata OReilly Superstream. Since the Strata in-person conference got canceled, the fantastic folks at OReilly organized an extremely well-attended…

LeadCrunch-case-study

Case Study: Data Science at LeadCrunch

One of the biggest pain-points in real-world machine learning is to consistently and rapidly putting models into production. When LeadCrunch[ai] approached Verta, their data science team was only able to deploy about two models annually. After successfully…

ML-Infrastructure--Build-vs.-Buy-vs.-Open-Source

ML-Infrastructure: Build vs. Buy vs. Open-Source

Notes from TWIMLCon’s Unconference session

How to move fast in AI without breaking things

Model Versioning, Tracking, and Spreadsheets.

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Introducing Verta

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