Domino Data Science Blog

Data Science Trends, Tools, and Best Practices

Posts tagged with:   Machine Learning

The Machine Learning Reproducibility Crisis

Pete Warden is the Technical Lead on the TensorFlow Mobile Embedded Team at Google doing Deep Learning. He is formerly the CTO of...read more

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Reproducible Machine Learning with Jupyter and Quilt

In this guest blog post, Aneesh Karve, Co-founder and CTO of Quilt, demonstrates how Quilt works in conjunction with Domino's Reproducibility Engine 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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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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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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Numenta Anomaly Benchmark: A Benchmark for Streaming Anomaly Detection

Written by Subutai Ahmad, VP Research at Numenta. With sensors invading our everyday lives, we are seeing an exponential increase in the availability...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

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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