Tagged "math"

Finding Nash Equilibria in Jeopardy!

Spoiler Alert: It’s unusual for post about a game show like Jeopardy! to have a spoiler, but if you are a die hard fan of the show and haven’t seen the second semifinal game of season 2 of Pop Culture Jeopardy! (it’s on Netflix), then don’t read this just yet.

(Here on I’m just going to write Jeopardy without the exclamation mark, for convenience.)


The last round in a game of Jeopardy is called “Final Jeopardy”. When the round begins, the three contestants (individually, usually, but in the case of Pop Culture Jeopardy, teams of two) are shown the category of the final clue.

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A Geometric Proof of the Perceptron Convergence Theorem

The last time I studied neural networks in detail was five years ago in college. I did touch upon backpropagation when Andrew Ng’s machine learning MOOC was offered on Coursera for the first time, but beyond that I’ve only dabbled with them through keras. Then recently, when I read about Coursera’s imminent decision to pull down much of their freely available material (you can read a rant about it here), I went on a downloading spree (many thanks to the wonderful coursera-dl). Of all the courses I downloaded, the one that caught my eye was Geoffrey Hinton’s course on Neural Networks for Machine Learning. Because of that and the fact that there were some computer vision projects going on at work, I decided to dive right in.

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