True or False: You can use bigger strides in a convolutional layer instead of a max-pooling layer for better accuracy.2 pointsTrueFalse

False. Using bigger strides in a convolutional layer instead of a max-pooling layer does not necessarily lead to better accuracy. Stride size and pooling are hyperparameters of the model and their optimal values depend on the specific task and data. They should be determined based on validation performance. Stride size in convolutional layer controls how the filter convolves around the input volume. In general, larger strides might result in loss of information, while smaller strides may retain more information. Max-pooling layer, on the other hand, is used to reduce the spatial dimensions of the output volume. It does not have any parameters to learn, making the network less prone to overfitting.