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How to get the equation that a multiple linear regression model is using in Keras w/ Tensorflow?

I have the weights and biases for both the normalizer and the
Dense layer in my model, but I am unsure how to convert these
values into 1 equation that the computer is using to predict
values, which I would like to know. The model takes 2 independent
values and predicts 1 value, so using the weights and biases below,
how I could formulate an equation:

weights for normalizer layer: [ 8.89 11.5 ]

biases for normalizer layer: [321.69 357.53]

(not even sure if the normalizer biases and weights matter as it
is part of preprocessing)

weights for Dense layer: [[ 0.08] [19.3 ]]

biases for Dense layer: [11.54]

Thank you very much and I would greatly appreciate any help!
🙂

submitted by /u/HexadecimalHero

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