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Teach a perceptron which letters are vowels with numpy/flask
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Perceptron Learning

A perceptron is the simplest form of 'neural network' learning.

The 'neuron' is simply a vector that can be multiplied against data points to say 1 or 0.

This perceptron tries to learn which letters are vowels, ie, we draw 26 points in space and say some are one class and the rest are another.

Visualization App

You can:

  • select what letter (or groups of letters) to feed to the perceptron next
  • watch it's learning pattern (initially, moving left after consonants, right after vowels)
  • see the weight vector at bottom of page
  • see the current accuracy as compared to a benchmark accuracy from a linear algebra class separation solution (LDA)
  • adjust the dimensionality

To run

Requires numpy/scipy (if you need these look up anaconda distribution)

Install python dependencies with

pip install .

from base directory.

Build JS app from viz directory

npm install
npm run build

After building, /voweler/dist/ should exist

Run python to run app simply.

Cross-request state persistence is available via shared memory managed by uwsgi: see the multiapp branch

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