Last active
December 10, 2020 15:23
-
-
Save NatuMyers/a55cef9193095ce5485893ee7ca6ffab to your computer and use it in GitHub Desktop.
Tensorflow.js Linear Regression
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
<html> | |
<head> | |
<title>Tensor Flow</title> | |
<script src="https://cdn.jsdelivr.net/npm/@tensorflow/tfjs@0.6.1"></script> | |
<script> | |
const nr_epochs=2048; // higher=better but slower | |
var tfinterface; | |
const model = tf.sequential(); | |
function initTF() { | |
// 1. TRAINING DATA - learn this 10x table | |
const xs = tf.tensor2d([1,2,3,4,5], [5,1]); | |
const ys = tf.tensor2d([10,20,30,40,50], [5,1]); | |
// 2. ML MODEL - linear regression model | |
model.add(tf.layers.dense({units: 1, inputShape: [1]})); | |
// Prep for training | |
model.compile({loss: 'meanSquaredError', optimizer: 'sgd'}); | |
// train -- the higher the number the more accurate you'll get (but longer run time) | |
tfinterface=model.fit(xs,ys,{epochs: nr_epochs}); | |
} | |
// 3. WRAPPER AROUND PREDICT | |
function predict(n) { | |
return tfinterface.then(()=> { return model.predict(tf.tensor2d([n],[1,1])); }); | |
} | |
// Helper for form | |
function formpredict(v,r) { | |
predict(v).then(function(res) { | |
// alert(res.get([0])); | |
r.innerHTML=res.get([0]); | |
}); | |
} | |
</script> | |
</head> | |
<!-- HTML --> | |
<body onLoad='initTF();'> | |
<p> | |
<div id='res'>Wait</div> | |
<p> | |
<form name='iForm' onSubmit='formpredict(this.val.value,document.getElementById("res")); return false;')> | |
<script> | |
document.getElementById("res").innerHTML=" "; | |
</script> | |
Input Number: <input name='val'><input type=submit> | |
</form> | |
</body> | |
</html> |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment