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In section 01-numpy the following statement deals with array arithmetics:
If, instead of taking an array and doing arithmetic with a single value (as above), you did the arithmetic operation with another array of the same shape, the operation will be done on corresponding elements of the two arrays.
It may be useful to mention that this is different from proper matrix multiplication which can be performed with numpy if you convert the array to a matrix object.
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@maxim-belkin that's exactly the point I was trying to make. particularly people who are used to MATLAB, where matrix multiplication is the default for two-dimensional arrays, the behaviour of Python may be surprising.
I think one sentence just saying it is not matrix multiplication but element wise multiplication would be sufficient. if you want to be perfect you would also link the words "matrix multiplication" to the documentation of how that works with numpy ;-).
While difference between element-wise multiplication and cross products is significant, I'm not sure we should talk about it while explaining the material. How about we add a note about element-wise multiplication vs cross product to instructor notes?