tensorflow.js is a JavaScript library for training and deploying ML models in the browser and on node.js.

tensorflow.js via node.js on Mac

In order to run tensorflow.js in node.js on Mac, you should install tensorflow.js as following:

$ npm install @tensorflow/tfjs-node


If your system NVIDIA GPU, it will be recommended to install below package as well.

$ npm install @tensorflow/tfjs-node-gpu


The below is the example of tensorflow.js based on node.js

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

// Load the binding:
require('@tensorflow/tfjs-node');  // Use '@tensorflow/tfjs-node-gpu' if running with GPU.

// Train a simple model:
const model = tf.sequential();
model.add(tf.layers.dense({units: 100, activation: 'relu', inputShape: [10]}));
model.add(tf.layers.dense({units: 1, activation: 'linear'}));
model.compile({optimizer: 'sgd', loss: 'meanSquaredError'});

const xs = tf.randomNormal([100, 10]);
const ys = tf.randomNormal([100, 1]);

model.fit(xs, ys, {
  epochs: 100,
  callbacks: {
    onEpochEnd: async (epoch, log) => {
      console.log(`Epoch ${epoch}: loss = ${log.loss}`);
    }
  }
});

tensorflow.js via script tag

The below is the example of Tensorflow.js coding as a part of HTML documentation.

tensorflow-example.html
<html>
  <head>
    <!-- Load TensorFlow.js -->
    <script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@0.13.3/dist/tf.min.js"> </script>

    <!-- Place your code in the script tag below. You can also use an external .js file -->
    <script>
      // Notice there is no 'import' statement. 'tf' is available on the index-page
      // because of the script tag above.

      // 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, {epochs: 10}).then(() => {
        // Use the model to do inference on a data point the model hasn't seen before:
        // Open the browser devtools to see the output
        model.predict(tf.tensor2d([5], [1, 1])).print();
      });
    </script>
  </head>

  <body>
  </body>
</html>



Reference URL: https://js.tensorflow.org/