Understanding dimensions of matrixes when are are m sample with n features

If there are 3 input features, 4 neurons in the first layer and 1 neuron in the final output layer. Then these are the dimensions

x is 3*1

w[1] is 4*3

b[1] is 4*1

a[1] is 4*1

w[2] is 1*4

b[2] is 1*1

a[2] is 1*1

Am I correct in saying that these dimensions would not change, if there are now 5 examples?

The dimensions of the weights and biases do not depend on the number of examples.

Say if X was size (m x n) and w was size (n x 1), then the product would be (m x 1).

‘m’ has no impact on the size of ‘w’.

got it, thnx