Domino Data Science Blog

Data Science Trends, Tools, and Best Practices

Posts tagged with:   machine learning

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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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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AI in the Enterprise: Making Corporations Smart Again

In this Data Science Popup session, Danny Lange, VP of AI and Machine Learning at Unity Technologies, gives an inside look at practical...read more

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Exploring the Limits of Parallelized Machine Learning

This week, Domino’s Chief Data Scientist, Eduardo Ariño de la Rubia, presented a webinar: Machine Learning at Scale with Amazon's X1 Instance. If...read more

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How Buzzfeed Uses Real-Time Machine Learning to Choose Their Viral Content

This talk took place at the Domino Data Science Pop-up in Los Angeles, CA on September 14, 2016. In this presentation, Jane Kelly,...read more

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Wisdom From Machine Learning at Netflix

At Data By The Bay in May, we saw a great talk by Netflix's Justin Basilico: Recommendations for Building Machine Learning Software. Justin...read more

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A Summary of Using k-NN in Production

This week, Domino’s Chief Data Scientist, Eduardo Ariño de la Rubia, presented a webinar: An Introduction to Using k-NN in Production. If you...read more

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Choosing Content for Netflix: How Data Leads the Way

This talk took place at the Domino Data Science Pop-up in Los Angeles, CA on September 14, 2016 In this presentation, Paul Ellwood,...read more

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Model-Based Machine Learning and Probabilistic Programming in RStan

In this recorded webcast, Daniel Emaasit introduces model-based machine learning and related concepts, practices and tools such as Bayes' Theorem, probabilistic programming, and...read more

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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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Getting error bounds on classification metrics

This is a guest post by Casson Stallings. The project (code, data, and results) is publicly available on Domino. Error bounds, or lack...read more

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