parameters given a data set and a set of meta parameters and for now we're going to be using deterministic or point estimate of this function key we told to note as f theta and of course we'll get back to Bayesian methods later and so we'll see Bayes a bit later okay so how do you actually try to design a neural network to do this well one thing you could do is you could use a recurrent neural network that takes in data points sequentially and produces a set of parameters Phi and so this recurrent neural network in this case will be