You want to solve a classification task. You first train your network on $20$

samples. Training converges, but the training loss is very high. You then

decide to train this network on $10,000$ examples. Is your approach to fixing

the problem correct? If yes, explain the most likely results of training with

$10,000$ examples. If not, give a solution to this problem.