Domino Data Science Blog

At the Intersection of Data Science and Engineering

An Introduction to Model-Based Machine Learning

This guest post was written by Daniel Emaasit, a Ph.D Student of Transportation Engineering at the University of Nevada, Las Vegas. Daniel's research...read more

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Providing Digital Provenance: from Modeling through Production

At last week's useR! R User conference, I spoke on digital provenance, the importance of reproducible research, and how Domino has solved many...read more

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Announcing Enhanced Apache Spark Support

Domino now offers data scientists a simple, yet incredibly powerful way to conduct quantitative work using Apache Spark. Apache Spark has captured the...read more

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Announcing: Data Science Pop-up Los Angeles

We're proud to announce Data Science Pop-up Los Angeles, the 5th event in our Data Science Pop-up series. Being held in L.A., the...read more

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Orchestrating Pipelines with Luigi and Domino

Building a data pipeline may sound like a daunting task. In this post, we will examine how you can use Luigi - a...read more

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The ugly little bits of the data science process

This morning there was a great conversation on Twitter, kicked off by Hadley Wickham, about one of the ugly little bits of the...read more

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Moving Academic Researchers into a Corporate Data Science World

This webinar was recorded on May 25, 2016 There are big cultural differences between data science practices in academic and corporate settings. For...read more

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Better knowledge management for data science teams

We’re excited to announce a set of big new features that make it easier for you to find and reuse past data science...read more

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Building and Delivering Risk Models to Global Insurance Companies

We’re excited to share our latest customer case study, about how KatRisk, a leading catastrophe risk modeling firm, used Domino to deploy its...read more

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“Unit testing” for data science

An interesting topic we often hear data science organizations talk about is “unit testing.” It’s a longstanding best practice for building software, but...read more

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Data Science: Just One More Way That Donald Trump is Different

If you’re a data scientist interested in working in politics, don’t bother applying to the Trump campaign — but Hillary has a job...read more

Using R and Python for Common SAS Functions

SAS is the recognized incumbent in the analytics, statistics and data science tool space. As the software celebrates its 50th birthday this year,...read more

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[Video] Making data science FAST: Survey of GPU accelerated tools

This talk took place at the Domino Data Science Pop-up in Austin, TX on April 13, 2016 In this talk, Mazhar Memon, CEO...read more

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The R Data I/O Shootout

We pit newcomer R data I/O package, feather, against popular packages data.table, readr, and the venerable saveRDS/writeRDS functions from base R. While feather...read more

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[Video] How Machine Learning Amplifies Inequality in Society

This talk took place at the Domino Data Science Pop-up in Austin, TX on April 13, 2016 In this talk, Mike Williams, Research...read more

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Visualizing Machine Learning with Plotly and Domino

This post was contributed by Chelsea Douglas, a Software Engineer at Plotly. Want to play with the code from this post? Visit the...read more

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