y is the set of training outputs (labels) y (1) , y (2) , ..., y (m) θ ← 0 repeat til done # see caption For each training tuple (x (i) , y (i) ) (in random order) 1. Optional (for reporting): # How are we doing on this tuple? Computeŷ (i) = f (x (i) ; θ ) # What is our estimated outputŷ? Compute the loss L(ŷ (i) , y (i) ) # How far off isŷ (i) from the true output