full-time programmer transitioning to creative-coder & content-creator
Published
Edited
Jun 7, 2022
Tensorflow JS Example
via https://medium.com/geekculture/machine-learning-modeling-or-xor-with-tensorflowjs-d9c03c5bd17ehttps://medium.com/geekculture/machine-learning-modeling-or-xor-with-tensorflowjs-d9c03c5bd17e
model = tf.sequential();
input = [[0, 0], [1, 0], [0, 1], [1, 1]];
inputTensor = tf.tensor(input, [input.length, 2]);
lossHistory = []
initModel = function*(model) {
lossHistory.length = 0
const output = [[0], [1], [1], [0]]
const outputTensor = tf.tensor(output, [output.length, 1]);
//input + 1 hidden layer
model.add(
tf.layers.dense({
inputShape: [2],
units: 2,
activation: 'sigmoid'
})
);
//output
model.add(
tf.layers.dense({
units: 1,
activation: 'sigmoid'
})
)
model.compile({
optimizer: tf.train.adam(0.1),
loss: 'meanSquaredError'
});
yield "training..."
model.fit(inputTensor, outputTensor, {
epochs: 1000,
shuffle: true,
callbacks: {
onEpochEnd: async (epoch, { loss }) => {
lossHistory.push(loss)
//await new Promises.delay(100)
// any actions on during any epoch of training
//await tf.nextFrame();
}
}
})
yield model
return model
}
{
for(let step of initModel(model)){
yield step ?? '?'
}
}
prediction = model?.predict(inputTensor)?.arraySync() ?? []
sparkline(lossHistory,800,200)
tf = import("https://cdn.skypack.dev/@tensorflow/tfjs@2")
import {sparkline} from "d4d66ef8e0b4d4f4"
useState = React.useState
import {React} from "@hastebrot/react@356"
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.
