Created
June 4, 2018 01:06
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Tensorflow Getting Started Example (https://js.tensorflow.org/#getting-started)
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| <html> | |
| <head> | |
| <!-- Load TensorFlow.js --> | |
| <script src="https://cdn.jsdelivr.net/npm/@tensorflow/[email protected]"> </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).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> |
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