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    0.1.2-beta.5 • Public • Published


    A JavaScript library for feature engineering on datasets, it helps you to cook trainable datus out as its name, datacook.

    Getting started

    Install datacook via NPM:

    npm install @pipcook/datacook --save

    And write your first example:

    import { Image } from '@pipcook/datacook';
    const dog = Image.read('test/node/image/artifacts/dog.jpg');
    const data = [ ...img.resize(100, 100).data ];  // the 100x100 data.

    Build your own word2vec model:

    import { Text } from '@pipcook/datacook';
    const text = 'The king is a man who rules over a nation, he always have a woman beside him called the\
     queen.\n she helps the king controls the affars of the nation.\n Perhaps, she acclaimed the position of a king\
     when the king her husband is deceased.'.split('\n');
    const stopWords = [ 'a', 'in', 'when', 'the', 'of', 'is', 'who' ];
    const word2vec = new Text.Word2Vec(text, 5, stopWords);
    // train the model
    await word2vec.train();
    word2vec.similarity('king', 'man'); // < 1.0
    word2vec.mostSimilar('king'); // returns words and its weights.


    To contribute to datacook, start from forking the repository, then clone to your local machine:

    $ git clone https://github.com/imgcook/datacook.git
    $ cd datacook

    Install dependencies:

    $ npm install

    Run tests for both Node.js and browser environment:

    npm run test

    To run specific tests:

    $ npm run test:node     # Node.js
    $ npm run test:browser  # Browser

    To build the source code to the dist folder, run:

    $ npm run build


    Apache 2.0


    npm i @pipcook/datacook

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