0
1
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We just wrote a mathematical expression for this line and this is our function, X
1

2
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plus (by) plus C equals to zero.
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Let's just write it in another way.
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We can also write this one as A over C, X, plus B or C, Y, class C/C, which is one equal
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to zero or later we can just replace.
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this was alpha and beta... 
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Y plus one equals to zero.
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8
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We can see that we have only two parameters which matter.
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9
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They are X and Y.
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Take a look at this example here we have X, Y and C and these two parameters which matters for us.
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11
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They're very important.
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12
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are X and Y, each of them has a specific weight.
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13
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You can say this is the weight of (x) is (a) in the first example, you can show it with the Alpha or with
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the beta. So the weight of X is shown with A and then here the rate of Y is surely B here we have a
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15
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fixed parameter which is C sum of all of them.
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If we send them to a sigma and it will give us the index, this one would be our index or sometimes
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17
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called net.
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This is giving us a signal, an index signal or a net signal.
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And later, if we just take the function of the net, we can already say if this patient is diabetic or it's
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not and it's healthy, you can show the result An, the output illogical output of zero or one here.
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21
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That's the expression for function F F of net.
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This is one whenever indignance is greater or equal than zero or better to say, whenever the net is
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positive in this side, this is positive, greater or equal to zero point is equal.
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24
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We can decide later based on our situation.
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25
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It can be for this part, for the negative part, or we can be for the positive part.
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Suppose there is a patient who is exactly on this line, then it's up to the doctor to decide if he
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or she will consider it as a diabetic person.
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Or we can still say to the person is fine and healthy. It shows a mathematical model of a neuron and we
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can call it a binary linear classification.
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I remember the example which we want to decide either to laugh at this picture or not.
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We were receiving some data and our brain, each neuron, will decide to activate or fire or not.
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So in the end, this neuron is processing some data and sending out a result.
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We can show it with 0 and 1 and later we can actually sure show it with more than zero and one parameters,
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more parameters.