00:35 step #0 randomly initialize weights w0, w1, w2, and w3
00:45 step #1 calculate weighted sum
01:00 step #2 apply activation function
01:18 step #3 determine error
01:54 'learning rate' is the rate at which the neural network learns (ranges from 0 to 1)
01:27 step #4 adjust weights
02:31 objective here is to determine what weights would
lead to 'Target Result' = 'Result' for all vectors in training data
02:02 repeat steps 1 to 4 until error = 0
03:32 demo prebuilt version of the app.
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quickly download, import into Eclipse, and run zip file for
'Neural Networks w/ JAVA - Tutorial 04'
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download source code @ https://sites.fastspring.com/prototypeprj/instant/2020
download source code @ https://sites.fastspring.com/prototypeprj/instant/all
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