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The first step is to define how a model will be specified to the engine. To get the ball rolling, here is how pyMC3 defines a model and runs inference:
with pm.Model() as model:
mu = pm.Normal('mu', mu=0, sd=1)
obs = pm.Normal('observations', mu=mu, sd=0.1, observed=y)
trace = sample(2000, cores=2) # Automatically runs the inference using NUTSReactions are currently unavailable
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