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<!DOCTYPE html>
<html>
<head>
<meta charset="utf-8" />
<meta http-equiv="X-UA-Compatible" content="IE=edge" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<title>AI "Hello, World" in TensorFlow.js</title>
<!-- Import TensorFlow.js -->
<script src="https://cdn.jsdelivr.net/npm/@tensorflow/[email protected]/dist/tf.min.js"></script>
<!-- Import tfjs-vis -->
<script src="https://cdn.jsdelivr.net/npm/@tensorflow/[email protected]/dist/tfjs-vis.umd.min.js"></script>
<!-- Import the main script file -->
<script src="script.js" type="module"></script>
<!-- Add styles -->
<link rel="stylesheet" href="style.css" />
</head>
<body>
<main>
<h1></a>AI "Hello, World" in TensorFlow.js</h1>
<p><a href="https://acmcsuf.com/ai-hello-world">Slides</a> | <a href="https://github.com/acmcsufoss/ai-hello-world">Code on GitHub</a></p>
<p>
Digit classification with the MNIST dataset is widely considered to be
the "Hello, World" of AI/machine learning projects. This is a simple example of
how to build and train a neural network to recognize handwritten digits
using TensorFlow.js.
</p>
<div class="drawn-digit-input-container"></div>
<hr>
<footer>
<p>
Made with ❤️ <a href="https://github.com/acmcsufoss"><strong>@acmcsufoss</strong></a>
</p>
</footer>
</main>
</body>
</html>