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Jonas Almeida
NCI/DCEG Chief Data Scientist
Published
Edited
Nov 17, 2021
2 stars
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model.save("localstorage://my-model-1")
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model.save("")
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x = tf.tensor2d([1, 2, 3, 4, 5, 6, 7], [7, 1])
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inputTensor = tf.tensor2d(
cars.map((d) => d.horsepower),
[cars.length, 1]
)
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labelTensor = tf.tensor2d(
cars.map((d) => d.mpg),
[cars.length, 1]
)
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inputMax = inputTensor.max()
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inputMin = inputTensor.min()
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[stats.max(cars.map((d) => d.horsepower)), stats.max(cars.map((d) => d.mpg))]
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normalizedInputs = inputTensor.sub(inputMin).div(inputMax.sub(inputMin))
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normalizedInputs.data()
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Plotly.newPlot(DOM.element("div"), [
{
x: (await normalizedInputs.array()).map((d) => d[0]),
type: "histogram"
}
])
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arr = (await normalizedInputs.array()).map((d) => d[0])
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arr.slice(0, 4).map
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