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Can someone help explain the dot product in machine learning?
Sorry if this isn't the right place to ask, but there are literally no Q/A or good tutorials about this. Why does the neural network tutorial use the dot product? What does it do/mean? How do you right it and what is the point? Everytime I search, it comes up with random maths and trigonometry, is there an easy definition?
10 ответов
+ 1
Ore Clueless Coder Actually I am wrong. The dot product is a scalar that is the sum of product of corresponding numbers in a vector.
[a , b , c] • [d , e , f] = ad + be + cf
Example:
[1,2] • [3,4] = 1.3 + 2.4 = 11
Sorry for the wrong Info.
+ 2
The dot product is the scalar product of two vectors. It is defined thus,
(aî + bj) • (cî + dj) = (ac) + (bd)
It is that simple
+ 2
Ćheyat read my answer again. FYI, (ac) + (bd) is same as ac + bd
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Clueless Coder Yes. That is why it is called scalar product. It transforms two or more vectors to a single scalar value.
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Ćheyat you don't have to beat yourself up about a little mistake. Everyone makes mistakes
+ 1
Ore Thanks, to me it isn't simple.
+ 1
Ore Yes I was wrong. Clueless Coder Yes
+ 1
Well that was an awkward mistake. 😆
0
Robin Thanks for the clarification, that was my last question about why it was so simple here but absolutely nuts everywhere else