Consider the following data samples: input desired label X1 X3 0 0 1 -1 0 1 0 -1 1 0 0 -1 1 0 1 1 1 1 0 1 0 1 1 1 1. Use gradient descent learning to train a classifier for this data. Assume the learning rate is 0.1. Initialize the weights to O's. Perform only one iteration; however, report the updated weights for iteration 2. 2. Calculate the loss at iterations 1 and 2. How does the change from the first to the second iteration compare to your expectation? Consider the following data samples: input desired label X1 X3 0 0 1 -1 0 1 0 -1 1 0 0 -1 1 0 1 1 1 1 0 1 0 1 1 1 1. Use gradient descent learning to train a classifier for this data. Assume the learning rate is 0.1. Initialize the weights to O's. Perform only one iteration; however, report the updated weights for iteration 2. 2. Calculate the loss at iterations 1 and 2. How does the change from the first to the second iteration compare to your expectation