TensorFlow Models

A JavaScript Library for

Training and Deploying

Machine Learning Models

In the Browser

Tensorflow Models

Models and

Layers are important building blocks in

Models and different types of

A TensorFlow

Model is a

Neural Network with one or more

A Tensorflow Project

Collecting Data

Creating a Model

Adding Layers to the Model

Compiling the Model

Training the Model

Using the Model

Example

Y = 1.2X + 5
Then you could calculate any y value with the JavaScript formula:

y = 1.2 * x + 5;

Note

// Create Training Data const xs = tf.tensor([0, 1, 2, 3, 4]);
const ys = xs.mul(1.2).add(5);
// Define a Linear Regression Model const model = tf.sequential();
model.add(tf.layers.dense({units:1, inputShape:[1]}));
// Specify Loss and Optimizer model.compile({loss:'meanSquaredError', optimizer:'sgd'});
// Train the Model model.fit(xs, ys, {epochs:500}).then(() => {myFunction()});
// Use the Model function myFunction() {
const xMax = 10;
const xArr = [];
const yArr = [];
for (let x = 0; x <= xMax; x++) {
let result = model.predict(tf.tensor([Number(x)]));
result.data().then(y => {
xArr.push(x);
yArr.push(Number(y));
if (x == xMax) {plot(xArr, yArr)};
});
}
}

The example is explained below:

Collecting Data

const xs = tf.tensor([0, 1, 2, 3, 4]);
Create a tensor (ys) with 5 correct y answers (multiply xs with 1.2 and add 5):
const ys = xs.mul(1.2).add(5);

Creating a Model

const model = tf.sequential();