For example, the feature vector and ground-truth label of the first instance is [3,6,5] and 7, respectively. Suppose we use a linear predictor f=wx+w0 to fit the data, with Squared Loss as the loss function. Complete the codes in "hw1_stochasticGradientDescent2.py", and solve w and w0 using stochastic gradient descent