Tag: Model Production

Collaboration Between Data Science and Data Engineering: True or False?

This blog post includes candid insights about addressing tension points that arise when people collaborate on developing and deploying models. Domino’s Head of Content sat down...

Themes and Conferences per Pacoid, Episode 1

Introduction: New Monthly Series! Welcome to a new monthly series! I’ll summarize highlights from recent industry conferences, new open source projects, interesting research, great examples, amazing...

Model Management and the Era of the Model-Driven Business

Over the past few years, we’ve seen a new community of data science leaders emerge. Regardless of their industry, we have heard three themes emerge over...

Put Models at the Core of Business Processes

At Rev, Nick Elprin, Domino's CEO, continued to provide insights on managing data science based upon years of candid discussions with customers. He also delved into...

Model Evaluation

This Domino Data Science Field Note provides some highlights of Alice Zheng’s report, "Evaluating Machine Learning Models", including evaluation metrics for supervised learning models and offline...

The Machine Learning Reproducibility Crisis

Pete Warden is the Technical Lead on the TensorFlow Mobile Embedded Team at Google doing Deep Learning. He is formerly the CTO of Jetpac, which was...

Managing Data Science as a Capability

Nick Elprin, CEO at Domino, presented a 3-hour training workshop, “Managing Data Science in the Enterprise”, that provided practical insights and interactive breakouts. The learnings, anecdotes,...

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...

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....

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,...

What Your CIO Needs to Know about Data Science

What would you rather be doing? Data science or DevOps? As a data scientist, your CIO may hear from you that model deployment is a challenge...

Data Science != Software Engineering

Domino’s guide, “What Engineering Leaders Need to Know About Data Science”, provides insights to help engineering leaders increase data science productivity and decrease engineering time spent...

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. Background Domino lets users publish R...