Probabilistic Deep Learning: With Python, Keras and TensorFlow Probability by Oliver Dürr & Beate Sick & Elvis Murina

Author:Oliver Dürr & Beate Sick & Elvis Murina [Dürr, Oliver & Sick, Beate & Murina, Elvis]
Language: eng
Format: epub
Publisher: Manning Publications Co.
Published: 2020-11-08T23:00:00+00:00

Figure 5.4 The synthetic validation data along with the predicted probabilistic model for linear regression, which is the same as an NN without a hidden layer. The mean μx of the CPD is modeled by the NN, and the standard deviation is assumed to be a constant. The black solid line indicates the positions of μxi, and the dashed lines show the positions of the 0.025 and 0.975 quantiles.

Hands-on time Open http://mng.bz/zjNw . Step through the code to solve exercise 1 and follow the code while reading.

Use TFP to fit a linear model with a constant standard deviation.

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