How to Create a Neural Network with ml5JS?

Last Updated : 02 Sep, 2024

Creating a neural network might sound complex, but with ml5.js, it becomes much easier. This JavaScript library is built on top of TensorFlow.js, and it simplifies the process of adding machine learning to your web projects. This article helps to create a basic neural network using ml5.js. In the context of machine learning, a neural network takes input data, processes it through layers of "neurons," and outputs a prediction or classification.

Approach

Start by setting up the basic structure of your HTML file. This includes meta tags for character encoding and responsiveness.
Add the ml5JS library to your HTML file using a script tag. This library provides the tools needed to build and train neural networks.
Set up the configuration for your neural network, including the number of input and output neurons, the task type (regression or classification), and debugging options.
Initialize the neural network with ml5.js using the options you defined.
Supply the network with sample input-output pairs so it can learn from them.
Scale the input data to standardize its range, which helps improve training performance.
Train the network using the provided data for a specified number of epochs.
Use the trained model to make predictions on new input data and log the results to the console.

Example: This example shows the implementation of the above-explained approach.

HTML

<!DOCTYPE html>
<html lang="en">

<head>
    <meta charset="UTF-8">
    <meta name="viewport" 
          content="width=device-width, 
                   initial-scale=1.0">
    <title>Neural Network with ml5.js</title>
    <!-- Include the ml5.js library from an alternative CDN -->
    <script src=
"https://cdn.jsdelivr.net/npm/[email protected]/dist/ml5.min.js"></script>
</head>

<body>
    <h1>Neural Network Example</h1>
    <p>Open the console to see the results.</p>
    <!-- Link to the external JavaScript file -->
    <script src="script.js"></script>
</body>

</html>

JavaScript

// Define the neural network options
const options = {
    inputs: 2, // Number of input neurons
    outputs: 1, // Number of output neurons
    task: 'regression', // Task type: 'classification' or 'regression'
    debug: true // Enable debugging
};

// Create the neural network
const neuralNetwork = ml5.neuralNetwork(options);

// Add training data
neuralNetwork.addData([0, 0], [0]);
neuralNetwork.addData([0, 1], [1]);
neuralNetwork.addData([1, 0], [1]);
neuralNetwork.addData([1, 1], [0]);

// Normalize the data
neuralNetwork.normalizeData();

// Train the model
neuralNetwork.train({ epochs: 32 }, finishedTraining);

// Function to run after training
function finishedTraining() {
    console.log('Model trained!');
    // Make a prediction
    neuralNetwork.predict([0, 0], function (err, results) {
        console.log(results);
    });
}

Output:

Conclusion

Creating a neural network with ml5.js is straightforward. Start by setting up an HTML file to include the ml5.js library. Then, use JavaScript to define the network, provide it with training data, and train it. Finally, you can use the trained network to make predictions. These steps make it easy to add machine learning to your web applications.

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