JSFiddle - React, Tailwind, and code Playground

by Przemyslaw

HTML

<!-- Import @tensorflow/tfjs-core -->
<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-core"></script>

<!-- Adds the CPU backend to the global backend registry -->
<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs-backend-cpu"></script>

JavaScript

console.clear();

const run = async () => {
console.log(123);
  const model = tf.sequential();

  // Add a dense layer with 1 output unit.
  model.add(tf.layers.dense({units: 1, inputShape: [1]}));

  // Specify the loss type and optimizer for training.
  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.
  await model.fit(xs, ys, {epochs: 500});

  // After the training, perform inference.
  const output = model.predict(tf.tensor2d([[5]], [1, 1]));
  output.print();
  console.log(123456);
}

run();