How one simply engineered feature helps to predict U.S. Supreme Court decisions with 97% Accuracy

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Photo by Sora Shimazaki from Pexels

When Justice Amy Coney Barrett was confirmed to the United States Supreme Court on October 31, 2020, the Republican party let out a collective sigh of relief. A Conservative majority all but guaranteed a reversal of Roe v. Wade and other legislation that did not support the Republican agenda. Finally, the United States judicial branch could return to a sense of family values, limited government, a tax policy allowing for individual prosperity, and -

…Wait a second. Isn’t the U.S. Supreme Court supposed to be impartial?

40 individual justices have served on the US Supreme Court (affectionately known as SCOTUS)…


Getting Started

Using a Film → Broadway Regression Model To Demonstrate the Need for Good Data

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One missing data point (or letter!) can make all the difference (Photo by Franki Chamaki, Unsplash)

You don’t need a linear regressor to recognize one of the core tenants of data science — bad data leads to a bad study. This was vividly demonstrated in my second project with Metis data science bootcamp, a linear regression model designed to predict the gross of a Broadway play or musical adapted from a film based on the commercial success of said film. In this article, we’ll talk about data purity, and why a lack of it in this study led to a model that isn’t quite yet meant for the stage.

(For anyone interested in the nuts and…


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How geographic data analysis led to canvassing strategy for optimum impact and engagement

There isn’t much that will get New Yorkers talking quite as much as the MTA. The Mass Transit Authority encompasses the many trains, buses, and other forms of transit that keep the 22.82 square miles of Manhattan and beyond in motion. Whether you find peacefulness in the daily commute, or dread it while you sip your morning coffee, it’s a staple of the busy lifestyles in NYC. COVID-19 has substantially diminished my personal subway usage, so my first project with Metis brought pangs of nostalgia and, incidentally, more attention to the turnstiles than I ever thought possible.

For fellow data…


Picture a small, rotund, and gregarious version of me. If you knew me as an seven-year old, this shouldn’t be too hard; in case our acquaintance doesn’t go back two decades, feel free to reference the photo below:

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An eager and nerdy young man celebrating the autumnal season (with a sensible leg reveal)

What can I say? I’ve always enjoyed the Fall.

(If our acquaintance doesn’t go back one day, let alone twenty years, feel free to learn more about my journey so far at my website!)

Underneath that shimmering bowl cut and behind those tri-focal lenses was a very eager and malleable young mind. My greatest desire, at this point in my life, was…

Nick Wilders

NYC musician, Metis data scientist, ponderer. Aiming to amplify and harness the power of data utilization in arts and entertainment.

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