Junior Researcher @ German Research Center for AI
Published
Edited
Jun 17, 2019
2 stars
XY = {
var temp = [];
for (var i = 0; i < 10000; i++) {
temp.push([Math.floor(Math.random() * 100) + 100, Math.floor(Math.random() * 100) + 100]);
}
var temp2 = [];
for (let obj of temp){
temp2.push(obj[0] + obj[1]);
}
return [tf.tensor2d(temp, [10000, 2])
, tf.tensor2d(temp2, [10000, 1])];
}
y.toString();
tf_model = {
const tmp_model = await tf.loadLayersModel('https://gist.githubusercontent.com/mircopp/2324d49c93cf209fbc35b315b5ab9466/raw/6e344d568ab5c6ec659513f2d417e8da16a5d1e4/model.json');
tmp_model.compile({optimizer : 'adam',
loss : 'meanSquaredError',
metrics : ['mae']});
return tmp_model;
}
tf_model.predict(X).toString();
tf_model_2 = {
const tmp_model = await tf.loadLayersModel(new ModelLoader(JSON.stringify(model)));
return tmp_model;
}
tf_model_2.predict(X).toString();
tfjs_vis = require('https://bundle.run/@tensorflow/tfjs-vis@1.1.0')
Purpose-built for displays of data
Observable is your go-to platform for exploring data and creating expressive data visualizations. Use reactive JavaScript notebooks for prototyping and a collaborative canvas for visual data exploration and dashboard creation.
