Building a Neural Network from Scratch in JavaScript

Learn how to build a neural network from scratch in JavaScript using TensorFlow

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Neural networks are a powerful tool for solving a wide range of problems in machine learning and artificial intelligence. Building a neural network from scratch in JavaScript allows developers to understand the underlying concepts and mechanics of these models, and to implement them in web-based applications. In this article, we will show you how to build a simple neural network in JavaScript using the popular library TensorFlow.js.

Let us begin.

First, we need to import the TensorFlow.js library into our JavaScript project. We can do this by adding the following code to the head of our HTML file

<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@2.0.1/dist/tf.min.js"></script>

Next, we will define our neural network model. In this example, we will create a simple feedforward network with one input layer, one hidden layer, and one output layer.

const model = tf.sequential();

model.add(tf.layers.dense({
  units: 4,
  inputShape: [2],
  activation: 'sigmoid'
}));
model.add(tf.layers.dense({
  units: 1,
  activation: 'sigmoid'
}));