the model learns so that when it's given unseen data and it picks up patterns that don't follow what it learned then it will flag that as an anomaly cool so now we begin with defining our h2o deep learning estimator we pass it through a variety of parameters I'll just go through a few so the one being the model ID which is purely just the name of your auto encoder so when you do save it for reuse of later on you can reference it an activation function of ten and a few hidden layers then you chain your model over here now you savor your model cool