Neural networks are considered complicated and they are always explained using neurons and a brain function. But we do not need to learn how to brain works to understand Neural networks structure and how they operate. We can look as something people encounter in everyday life more often, like a corporation hierarchy.
Let us start with logistic regression. Recall that a logistic regression divides 2 sets by a line (or a hyperplane if we have higher dimensions)
The logistic regression yields values form 0 to 1, and we can consider the process as making a evaluation. In the process we get data and we calculate our evaluation by a formula.
For example we may have the following assignment: to compute if we have enough goods in storage to last for a week of sales. This is quite a common problem, and say some clerks report their numbers to their manager to figure it out. The manager collects information, processes it and makes an evaluation.
Note that this is how a logistic regression functions.
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It is a layout for logistic regression.
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