Title: **Building Intelligent Websites with TensorFlow.js in HTML**

Introduction

In this blog post, we will delve into the fascinating world of Artificial Intelligence (AI) and explore how to integrate it into websites using TensorFlow.js, a powerful JavaScript library. We will focus on HTML implementation, ensuring that our code is clean and minimal, without any CSS styling.

What is TensorFlow.js?

TensorFlow.js is an open-source JavaScript library for training and deploying ML models in the browser and on Node.js. It allows developers to build and train machine learning models, and then run them in the browser, making AI more accessible than ever.

Getting Started

To get started, you’ll need to include the TensorFlow.js library in your HTML file:

“`html

“`

Creating a Simple Model

Let’s create a simple linear regression model to predict the price of a house based on its area.

“`javascript
// Import TensorFlow.js
import * as tf from ‘@tensorflow/tfjs’;

// Create tensors for our data
const xs = tf.tensor2d([0, 500, 1000, 1500, 2000], [5, 1]);
const ys = tf.tensor2d([0, 180000, 313000, 403000, 480000], [5, 1]);

// Create a linear regression model
const model = tf.sequential();
model.add(tf.layers.dense({units: 1, inputShape: [1]}));

// Compile the model
model.compile({loss: ‘meanSquaredError’, optimizer: ‘sgd’});

// Train the model
model.fit(xs, ys, {epochs: 500});
“`

Predicting with the Model

Once the model is trained, you can use it to make predictions:

“`javascript
// Predict the price of a house with an area of 1200 square feet
const prediction = model.predict(tf.tensor2d([1200], [1, 1]));
prediction.print();
“`

Conclusion

With TensorFlow.js, you can bring the power of AI directly to your web applications. By using HTML for structure and JavaScript for functionality, you can create intelligent, interactive websites that engage users in new and exciting ways. Start exploring the possibilities today!