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how does a neural network work

HOW A NEURAL NET WORKS STEP BY STEP:

There is a matrix of nodes like this:

0 0 0
0 0 0
0 0 0

Inputs are fed in from the left. like this:

(.1) 0 0
(.24) 0 0		(inputs in parenthesis)
(0) 0 0

the next nodes data is calculated by multiplying A weight to each node 
in the layer before and then adding bias. And then putting in an 
activation function. Like this:

.1  ----(weight: 1)--> .1
.24 ----(weight: .5)--> .12  ----> .1 + .12 + 0 = .22 + bias
0   ----(weight: 2)-->  0


Each node has a bias, for this node lets say its .3

.22 + .3(bias) = .52

After all that you put it in an activation function.

tanh(.52) ---> data for the next node

Everything i showed above was just the caclulation for the 
first node in the second layer though so the matrix
would look like this
after all that.

.1 tanh(.52) 0
.24 0 0
0 0 0

Then you keep doing that for each layer until you reach the end.

Hope this helped?

(Q A)

Does each node have a weight?

No. Each connection has a weight. Or i guess you could say each node
has lots of weights each corresponding to a node in the last layer.


Does each node have a bias?
Yes each node has only one bias.


 
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Tagged: #neural #network #work
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