Jake Worth

Jake Worth

Neural Networking for Complete Sentences

Published: May 19, 2019 2 min read

This week I wrote a bit of neural networking code for the first time. It utilizes Brain.js to try and recognize if a sentence is grammatically complete.

Here’s my code.

const net = new brain.recurrent.LSTM()

  { input: "Hello, I'm John Walker.", output: 'complete' },
  { input: 'This is on you!', output: 'complete' },
  { input: 'John kik', output: 'incomplete' },
  { input: 'This is', output: 'incomplete' },
  { input: 'Great job.', output: 'complete' },
  { input: 'When I hear a', output: 'incomplete' },

What’s going on here? First, I instantiate an instance of Brain’s LSTM (Long Short-Term Memory). Then, I train it on a collection of sentences, telling the system if each is complete or incomplete. Even six examples is computationally expensive on a new iMac.

Here’s the output:

> net.run("I'm Stil.");
> net.run("Great job!")

It works for these examples, and fails for others. Why? Too small a dataset certainly. My solution was mostly a bit of hacking to answer this Stack Overflow question:

Brain js NaN

I’d like to explore neural networking in the future, when there’s a practical application driving me toward it.

Get better at programming by learning with me. Subscribe to my newsletter for weekly ideas, creations, and curated resources from across the world of programming. Join me today!