Demography and Subway Fares Part 1: MTA Fare Data

Note: This is part of a project I completed as part of a Data Mining class looking at using demographic data to predict fare type usage on the New York City Subway System. I’m publishing posts on the methods I used to analyze the data and the ultimate results in a series of blog posts. […]

Demography and Subway Fares: Introduction

This past Fall, I attempted to use US Census demographic data to predict fare-type usage on the New York City Subway system using a number of different machine learning algorithms.  The intention was to see if it was possible to predict the fare-type used at a particular subway station based on demographic information for the […]

In Praise of Simplicity

I’ve finally been able to start getting caught up on my podcasts and just listened to Walter Isaacson’s interview with Terry Gross on NPR’s Fresh Air (yes, I have podcasts from over a year ago I still haven’t listened to).  Pulling nuggets of wisdom and insight from Steve Job’s life is like finding seashells on the […]

Landmarks on the Road of Progress

As I mention in my About section, I consider myself a data scientist in training.  I worked as a data analyst and did about as much as a non-programmer can do with Excel, including creating macros, writing in-cell formulas, and pushing Pivot Tables to their upward limit of functionality.  I applied to graduate school in order […]

When the fundamentals really do matter (to 311 million Americans and the world)

What does it take to build a massive, never-before-seen behemoth of a campaign contribution and voter mobilization management platform? Millions of dollars spent on outside consultants to build from the top down or considerably less hiring an army of senior technologists to build from the bottom up? Anyone who’s read any of the post-election analysis of the respective systems […]