Numpy Array Broadcasting In Python Explained

How Numpy adds arrays of different shapes.

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[amaarquadri]

Thanks for making it intuitive! Maybe I won't have to mess around in a python console to figure stuff out every time this comes up now!

[LouisDuran]

Thanks for explanation. I have been learning ML and neural networks on Coursera and they did not explain broadcasting as well as you did.
The example of iteratively doing the adds on "incompatible" matrices and comparing to the answer given by numpy really helped a lot in my undersanding of broadcasting.

[siddhantkandi]

Thank you for making it interesting and easy to learn.

[mariabarbarasalinasluna]

Excellent video, you explain it perfectly, thanks a lot ;)

[ZeroSleap]

Huh i've been coding my own Math library in C# and i've tackled Matrix(array) operations, i defined the regular Matrix addition that requires same Matrix dimensions, but i could i add this too, thanks!

[LouisDuran]

@mCoding Have you done any work in the area of Machine Learning and Deep Neural Networks?

[ruroruro]

11:36 Disclaimer: Actually, you should avoid using reshape in most cases. Instead, try to always use

1) indexing with np.newaxis/None to add new "1" dimensions
2) x.squeeze(axis=N) to remove a "1" dimension in Nth position
3) x.transpose(...) or x.swapaxes(...) to change the order of axes
4) x.flat/flatten when you want to "stretch" your N-dim array into a flat 1D vector.

You should only really use reshape when you really actually want to change the shape, while also rearranging the order of the elements.
The reason for this recommendation is that it's very easy to make a mistake with reshape and still end up with "valid" code.
For example, np.ones(2, 3).reshape(3, 2) might look like it transposes the dimensions, but actually it "reinterprets" the shape of the array.
Additionally, reshape **sometimes** produces views of the original arrays and **sometimes** produces copies.

[htvyghh]

excellent video. btw, could you tell what the text font being used in this video?

[JoaoVitorBRgomes]

At 7:19 isn't y shape == (1, 3) ? And not (3, 1) ?

[rolininthemud]

My answer for the exercise at the end...




The array [[[[2]], [[3]], [[4]]]] which has shape (1, 3, 1, 1)

[ziweihuang]

For example 3, the shape of y should be (1, 1, 1, 1, 17) rather than (1, 7, 1, 1, 17)