Domino Data Science Blog

Data Science Trends, Tools, and Best Practices

Data for Good’s Inaugural Meetup: Peter Bull of DrivenData

Recently, Domino for Good hosted the inaugural meetup of the new group Data for Good. Over 40 data do-gooders came to see Peter Bull...read more

Domino for Good: Collaboration, Reproducibility, and Openness, in the Service of Societal Benefit

The Path of a Data Do-Gooder When I joined Domino Data Lab to lead the Domino for Good initiative a few months ago, it...read more

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Domino now supports JupyterLab — and so much more

You can now run JupyterLab in Domino, using a new Domino feature that lets data scientists specify any web-based tools they want to...read more

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Humans in the Loop

This guest blog post from Paco Nathan dives into how people and machines collaborating together to perform work is real and not science...read more

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Measuring Data Science Business Value

This blog post covers metrics that help data science leaders ensure their team’s work is aligned to business value. Data science managers and...read more

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New G3 Instances in AWS – Worth it for Machine Learning?

We benchmarked AWS’s new G3 instances for deep learning tasks and found they significantly outperform the older P2 instances. The new G3 instances...read more

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Quick Tips for Getting A Data Science Team Off the Ground

This blog post provides concise tips for leaders at startups and early-stage companies to consider when getting a data science team off the...read more

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Recommender Systems through Collaborative Filtering

This is a technical deep dive of the collaborative filtering algorithm and how to use it in practice. From Amazon recommending products you...read more

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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...read more

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Emotional Intelligence for Data Science Teams

We surveyed and interviewed some of our most successful customers to learn how they align their data science team with their business. The...read more

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Data Science in the Enterprise: Insights from eBay, Stitch Fix, Teleon Health, and RISELab

We recently hosted a panel discussion with several data science leaders about organizational design and tooling for enterprise data science. Watch the full...read 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 lets...read more

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Scaling Machine Learning to Modern Demands

This is a Data Science Popup session by Hristo Spassimirov Paskov, Founder & CEO of ThinkFast.   Summary Machine learning has revolutionized the...read more

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Improving Zillow’s Zestimate with 36 Lines of Code

Zillow and Kaggle recently started a $1 million competition to improve the Zestimate. We are releasing a public Domino project that uses H2O’s...read more

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Data Scientists are Analysts are Software Engineers

In this Data Science Popup session, W. Whipple Neely, Director of Data Science at Electronic Arts, explains why data scientists have responsibilities beyond...read more

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Horizontal Scaling for Parallel Experimentation

The amount of time data scientists spend waiting for experiment results is the difference between making incremental improvements and making significant advances. With...read more

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