Implement a Neural Network using Pytorch

Credit Card Approval. On one of the first lectures, a credit card approvalrecord with multiple predictors was used as an example to show the use-fulness of learning from data. Here you will have the chance to createyour own Neural Network based on CC data.csv. The data contains 15predictors, and one response (approved or denied). You’ll randomly splityour data into training and testing with a 80/20 ratio.(a) Implement a Neural Network using Pytorch with the following spec-ifications:? Input layer: Number of neurons as number of inputs (15).? Second layer: fully connected layer with N neurons.? Set the number of neurons for the second layer N , and the num-ber of epochs, to obtain an accuracy of at least 80% in the train-ing data.(b) Evaluate the model with the testing data, report the accuracy; com-pute and print the predicted decision for every input of the testingdata (approved or denied) alongside with the real labels.