Subject archive for "model-production," page 4
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
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
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
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 != Software Engineering
Why understanding key differences between data science and engineering matters
By Domino3 min read
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
Subscribe to the Domino Newsletter
Receive data science tips and tutorials from leading Data Science leaders, right to your inbox.
By submitting this form you agree to receive communications from Domino related to products and services in accordance with Domino's privacy policy and may opt-out at anytime.