class FFSNNetwork :

inside init :

self.sizes = [self.nx] + hidden_units + [self.ny]

for i in range(self.nh+1):

self.W[i+1] = np.random.randn(self.sizes[i], self.sizes[i+1])

self.B[i+1] = np.zeros((1, self.sizes[i+1]))

this code means it is being defined of shape (n_features x hidden_units)

but shouldn’t the weight matrix be of size ( hidden_units x n_features )