Can someone help explain the dot product in machine learning?

Question

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?

Answer 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.

Answer 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

Answer 3

Ćheyat read my answer again. FYI, (ac) + (bd) is same as ac + bd

Answer 4

OK, I think I get. Just to clarify: (a, b) • (c, d) = ac + bd is correct? Ore Ćheyat

Answer 5

Clueless Coder Yes. That is why it is called scalar product. It transforms two or more vectors to a single scalar value.

Answer 6

Ćheyat you don't have to beat yourself up about a little mistake. Everyone makes mistakes

Answer 7

Ore Thanks, to me it isn't simple.

Answer 8

Ore Yes I was wrong. Clueless Coder Yes

Answer 9

Well that was an awkward mistake. 😆

Answer 10

Robin Thanks for the clarification, that was my last question about why it was so simple here but absolutely nuts everywhere else