Suppose we obtain n labeled samples {(xi , yi)} n i=1 from our underlying distribution d. suppose we break this into ntrain and ntest samples for our training and test set. recall our definition of the true least squares error (f) = e(x, y)∼d[(f(x) − y) 2 ] (the subscript (x, y) ∼ d makes clear that our input-output pairs are sampled according to d). our training and test losses are defined as: btrain(f) = 1 ntrain x (x, y)∈training set (f(x) − y) 2 btest(f) = 1 ntest x (x, y)∈test set (f(x) − y)

Install and use wireshark program ( send back screen shots and other vital information) case project 3-2: decode a tcp segment in a wireshark capture in this chapter, you walked through tcp segment to interpret the data included in its header. in this project, you use wireshark to capture your own http messafes, examine the tcp headers, and practice interpreting the data you'll find there. 1. open wireshark and snap the window to one side of your screen. open a browser and snap that window to the other side of your screen so you can see both windows.