Suppose you have a dataset with m = 50m=50 examples and n = 200000n=200000 features for each example. You want to use multivariate linear regression to fit the parameters \thetaθ to our data. Should you prefer gradient descent or the normal equation?

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Look at this pattern ; 1,4,9, number 10000 belongs in this pattern . what’s the place of this number?

Suppose that 3% of all athletes are using the endurance-enhancing hormone epo (you should be able to simply compute the percentage of all athletes that are not using epo). for our purposes, a “positive” test result is one that indicates presence of epo in an athlete’s bloodstream. the probability of a positive result, given the presence of epo is .99. the probability of a negative result, when epo is not present, is .90. what is the probability that a randomly selected athlete tests positive for epo? 0.0297