Subject archive for "predictive-models"

Machine Learning

How To Make Data-Driven Predictions with Predictive Modeling

When you hear words like machine learning (ML) or artificial intelligence (AI), one of the first things that comes to mind is correctly predicting future occurrences or answering difficult questions about the present based on past events. At its core, this is what predictive modeling is all about.

By David Weedmark8 min read

Data Science

Justified Algorithmic Forgiveness?

Last week, Paco Nathan referenced Julia Angwin’s recent Strata keynote that covered algorithmic bias. This Domino Data Science Field Note dives a bit deeper into some of the publicly available research regarding algorithmic accountability and forgiveness, specifically around a proprietary black box model used to predict the risk of recidivism, or whether someone will “relapse into criminal behavior”.

By Domino14 min read

Data Science

Item Response Theory in R for Survey Analysis

In this guest blog post, Derrick Higgins covers item response theory (IRT) and how data scientists can apply it within a project. As a complement to the guest blog post, there is also a demo within Domino.

By Derrick Higgins9 min read

Data Science

Data Science is more than Machine Learning 

This Domino Data Science Field Note provides highlights and video clips from Addhyan Pandey’s Domino Data Pop-Up talk, “Leveraging Data Science in the Automotive Industry.” Addhyan Pandey is the Principal Data Scientist at Highlights covered in this blog post include Pandey using word2vec to identify duplicate vehicles on the platform, how his data science team refers to predictive models as “data products”, and the company’s overall approach to data science. While this post covers highlights and video excerpts, the full video of his talk is available. If this type of content interests you, visit the Domino Data Science Pop-Up Playlist or consider attending Rev.

By Domino6 min read

Data Science

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.

By Alexandre Bergeron7 min read

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