Tensorflow.js Linear Regression
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<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> |
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