Domino Data Science Blog

Data Science Trends, Tools, and Best Practices

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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What Data Scientists Should Know About Hiring, Sharing, and Collaborating

In this post we summarize some of our most recent and favorite answers on Quora to questions from the community about hiring junior...read more

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Fighting Child Exploitation with Data Science

Every day, 100,000 new escort ads are posted online. That is according to Thorn, a nonprofit that fights child sexual exploitation through technology...read more

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Multicore Data Science with R and Python

This article is an excerpt from the full video on Multicore Data Science in R and Python. Watch the full video to learn...read more

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Imbalanced Datasets

Imagine you are a medical professional who is training a classifier to detect whether an individual has an extremely rare disease. You train...read more

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Git Integration in Domino

We recently released new functionality that provides first-class integration between Domino and git. This post describes the new feature, and describes our perspective...read more

Succeeding with Alternative Data and Machine Learning

Perhaps the biggest insight in feature engineering in the last decade was the realization that you could predict a person's behavior by understanding...read more

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