Please help with the r$-$code portion

Spambase data set is an example for classification for e$-$mail, Spam or Non$-$Spam. The last column of the data set determines whether the e$-$mail Spam or Non$-$Spam.

a$)$ Check whether spambase data set includes some missing values $($i$.$e NA$).$ Remove the observation if there is any missing value in the any characteristics of the corresponding observation.

b$)$ Choose $80\%$ of your data as training data set.

c$)$ Normalize the data and apply Neural Network algorithm with $1$ layer which has $10$ hidden neurons.

d$)$ Calculate the training error of Neural Network algorithm.

e$)$ Calculate the testing error of Neural Network algorithm.

f$)$ Apply Multilayer Neural Network algorithm with $3$ layers which have $5,3$ and $4$ hidden neurons, respectively.

g$)$ Calculate the training error of Multilayer Neural Network algorithm.

h$)$ Calculate the testing error of Multilayer Neural Network algorithm.

i$)$ Based on the training and testing errors, discuss which method performs better.