Domino Data Science Blog

Data Science Trends, Tools, and Best Practices

Posts tagged with:   engineering

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 more

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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 more

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Image diffing with CSS tricks

We've been hard at work delivering exciting new features in Domino. Our latest release included a lot, including the ability to import/share more

Faster model tuning and experimentation

Domino provides a great way to iterate on analytical models by letting you run many experiments in parallel on powerful hardware and more

Reflections on “buy vs build”

“Buy vs build”, “not-invented-here syndrome” and even “invented-here-syndrome” have been written about extensively. I want to share a few reflections on the topic, more


Building an open product for power users

This post describes our engineering philosophy of building an “open” product, i.e., one that supports existing tools and libraries, rather than building more

Cloud Security: The right way to worry

Here’s a question we hear a lot: We’re not that comfortable with the cloud from a security perspective -- can you install more

A mongo-based cache plugin for Play

A quick engineering-related post: we built a cache plugin for Play that uses capped collections in Mongo. It's available on Github if you' more

R Notebooks in the Cloud

We recently added a feature to Domino that lets you spin up an interactive R session on any class of hardware you choose, more