Subject archive for "model-production," page 4

Data Science

Data Quality Analytics

Scott Murdoch, PhD, Director of Data Science at HealthJoy, presents how data scientists can use distribution and modeling techniques to understand the pitfalls in their data and avoid making decisions based on dirty data.

By Domino17 min read

Data Science

Best Practices for Managing Data Science at Scale

We recently published a practical guide for data science management intended to help current and aspiring managers learn from the challenges and successes of industry leaders. This blog post provides a distilled summary of the guide.

By Mac Steele3 min read

Data Science

Answering Questions About Model Delivery on AWS at Strata

This post is a recap of the common questions Domino answered in the booth at Strata New York. We answered questions about access to EC2 machines, managing environments, and model delivery.

By Domino Data Lab7 min read

Data Science

What Your CIO Needs to Know about Data Science

What would you rather be doing? Data science or DevOps?

By Domino4 min read

Data Science

Data Science != Software Engineering

Why understanding key differences between data science and engineering matters

By Domino3 min read

Data Science

Model Deployment Powered by Kubernetes

In this article we explain how we’re using Kubernetes to enable data scientists to deploy predictive models as production-grade APIs.

By Alexandre Bergeron7 min read

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