Train Naive Based Classifier

For (a) I have calculated $P(G)=\frac{5}{8}$, $P(O|G)=\frac{2}{5}$, $P(B|G)=\frac{1}{5}$, $P(C|G)=\frac{4}{5}$, and $P(A|G)=\frac{4}{5}$. Now how do I calculate the maximum likelihood estimate of these values?

And how do I go about part (b)? I get that $O,B,C,A$ are independent so I can multiply them to get joint probability. But for values like $O_i$ for sample $i=9$, that is just $0$, since sample 9 doesn't have outdoor seating. And how am I supposed to calculate $P(G_i)$ if I don't know what $G_9$ is?