I don’t understand how np.dot(W.T, X) work on Numpy.
why W should to transpose and how dot work on this?
Could someone deep explain about this?
Thank u a lot 
Hi there,
np.dot(x, y) just multiplies 2 matrices, but to multiply these 2 matrices here you need certain sizes and the transpose is doing exactly that, otherwise it will give an error.
Check this video for matrix multiplication:
Thank a lot for your explain.
Could i ask another question the first time W get what a shape ? why should to transpose to match for X matrices.
Thank u
Ok Prof Andrew explains this very clearly here
In case of logistic regression both w and x have shape (n, 1) (for one example with n features) but in order to multiply them one needs to be transposed hence W.T.
In case of many examples both w and x are of shape (n, m) and again W is transposed.
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Thank u so much now I understand.
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