deeptea v0.0.3

Install with npm:

npm install --save deeptea

How about Yarn?

yarn add deeptea

This README reflects deeptea v0.0.x and greater currently

TL;DR

• Allows anyone to easily without a giant learning curve create beautiful deep learning / NLP-powered programs
• You can do it in under 10 lines of Javascript
• Built-in models taught to the neural network(s) to help kick-start creating
• Train your own natural language processing models, just supply an input and a category

Creating NLP-based bot in 10 lines or less

"use strict";
let deep = require('deeptea');
let Deeptea = deep;
let sampleInput = 'Hey there! I was outsied with my sister and dog when I stumbled upon a chess board! I remember I did have a computer virus, but I think I got rid of it.'; // intentional typo - yes, it understands your finger-thumbling
let demo = new Deeptea(sampleInput);
demo.run();
console.log(example_WordType.getNaturalType());

7 Lines. Booyah!

Creating NLP-based bot that'll respond to you, based on types

"use strict";
let deep = require('deeptea');
let Deeptea = deep;
let sampleInput = 'Hey there! I was outside with my sister and dog when I stumbled upon a chess board! I remember I did have a computer virus, but I think I got rid of it.';
let example_WordType = new Deeptea(sampleInput);
// OK, let's train and run the model(s)
example_WordType.run();
// Now we do logical processing
if(example_WordType.getNaturalType() === 'common-phrase-outdoor') {
  var reply = '';
  reply += 'Hey there!\n';
  let scope = example_WordType.getScope();
  if(scope.animals >= 1) {
    reply += 'I love that you have a pet! What\'s their name/names?\n';
  }
  reply += 'Thanks for the cool story!';
  console.log(reply);
}

OK, but how can I understand how it came to the conclusion of common-phrase-outdoor?

Breaking down the madness with 6 lines

Simply run these inputs, and you'll see the exact reasoning how it came to this conclusion:

console.log('Logical scope:');
console.log(example_WordType.getScope()); // ex: { computer: 8, animals: 4, ...}
console.log('Total scope:');
console.log(example_WordType.getTotalScope()); // ex: ['computer','computer'....]
console.log('Natural Type: ');
console.log(example_WordType.getNaturalType()); // ex: 'natural-outdoor-phrase--generic-package'
console.log('Keywords: ');
console.log(example_WordType.getKeywords()); // ex: ['dog', 'cat', 'computer virus', 'ransomware', 'wanacry', 'github', 'Terrain']

But we're still working on it. Stay tuned, help train our default models.

• Automatic Data Training
• Web Scraping (uses ADT above to train)
• Saving and making API-accessible endpoints