Given the following feecforward neural network with one hidden layer and one output layer, assuming the network initial weights are 1.0 Oa w1.0. All nodes use a sigmoid activation function with value bc 2.0, and the learning rate ? is set to 0.5. The expected output is 1 if an instance's dass label is "True", otherwise, the expected output is 0. Given the following three instances which are labeled as "True", "False", and "True", respectively, please calculate their actual outputs from the network? [0.5 pt] What is the mean squared error of the network with respect to the three instances? [0.5 pt] Assuming instance I, is fed to the network to update the weight, please update the network weight (using backpropogation rule) by using this instance (list major steps and results) [2.0 pts] 1.0 1.0 1.0 05 1.0 05 Given the following feecforward neural network with one hidden layer and one output layer, assuming the network initial weights are 1.0 Oa w1.0. All nodes use a sigmoid activation function with value bc 2.0, and the learning rate ? is set to 0.5. The expected output is 1 if an instance's dass label is "True", otherwise, the expected output is 0. Given the following three instances which are labeled as "True", "False", and "True", respectively, please calculate their actual outputs from the network? [0.5 pt] What is the mean squared error of the network with respect to the three instances? [0.5 pt] Assuming instance I, is fed to the network to update the weight, please update the network weight (using backpropogation rule) by using this instance (list major steps and results) [2.0 pts] 1.0 1.0 1.0 05 1.0 05