EPISODE · May 20, 2015 · 11 MIN
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from Linear Digressions · host Katie Malone
There’s a big difference between a table of numbers or statistics, and the underlying story that a human might tell about how those numbers were generated. Think about a baseball game—the game stats and a newspaper story are describing the same thing, but one is a good input for a machine learning algorithm and the other is a good story to read over your morning coffee. Data science and machine learning are starting to bridge this gap, taking the raw data on things like baseball games, financial scenarios, etc. and automatically writing human-readable stories that are increasingly indistinguishable from what a human would write. In this episode, we’ll talk about some examples of auto-generated content—you’ll be amazed at how sophisticated some of these reporter-bots can be. By the way, this summary was written by a human. (Or was it?)
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