Today I know TensorFlow.js is released that is a library train and use deep learning models directly in the browser, in JavaScript. Includes the full Keras API, and ability to load saved Keras models (and even fine-tune them in the browser)! So I learn it on the official page: https://js.tensorflow.org/

There’s a simple model in the page. So I try it by TDD style.

const tf = require('@tensorflow/tfjs');
const expect = require('chai').expect

describe(`A WebGL accelerated, browser based JavaScript library for training and deploying ML models`, () => {
    it(`train a simple model in TensorFlow.js`, (done) => {

        // Define a model for linear regression.
        const model = tf.sequential();
        model.add(tf.layers.dense({ units: 1, inputShape: [1] }));

        // Prepare the model for training: Specify the loss and the optimizer.
        model.compile({ loss: 'meanSquaredError', optimizer: 'sgd' });

        // Generate some synthetic data for training.
        const xs = tf.tensor2d([1, 2, 3, 4], [4, 1]);
        const ys = tf.tensor2d([1, 3, 5, 7], [4, 1]);

        // Train the model using the data.
        model.fit(xs, ys).then(() => {
            // Use the model to do inference on a data point the model hasn't seen before:
            // model.predict(tf.tensor2d([5], [1, 1])).print();
            const tensor = model.predict(tf.tensor2d([5], [1, 1]));
            expect(tensor.dataSync()[0]).to.be.greaterThan(7.9)
            done();
        }).catch((err) => done());
    });
});
=> test passed

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