Probabilistic Programming, Pyro, Data Science, Hands On Tutorials.
each normal distribution such that it agrees with our data as much as possible. >>> iter: 0, normalized loss:5.28 >>> iter: 250, normalized loss:-0.64 >>> iter: 500, normalized loss:-0.68 >>> iter: 750, normalized loss:-0.68 >>> iter: 1000, normalized loss:-0.68 >>> iter: 1250, normalized