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Nyt
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Building the Next New York Times Recommendation Engine
The NYT engineering blog's post on building their new recommendation engine — combining collaborative filtering with content-based signals to recommend articles. A rare look at production recommendation systems at a major media company before the algorithmic feed era fully arrived.
Code Academy as Career Game-Changer (NYT, 2015)
The New York Times profiling coding bootcamps as legitimate career changers in 2015 — a mainstream media validation moment that preceded the eventual credential inflation and quality variance problems that followed. Galvanize was prominently featured.
The PourOver Book — NYT's In-Browser Filtering Library
PourOver is an NYT-open-sourced JavaScript library for fast in-browser filtering and sorting of large collections. Built for news apps that need to let users slice thousands of items without server round-trips.