What Is A Neural Network?
INTRODUCTION
The concept of artificial neural networks has always been fascinating and puzzling for the computer science community. It’s a network inspired by living organisms, with the goal of mimicking human intelligence. As it turns out, that is not impossible but there are some limitations to it.
One major hurdle to learning machine learning is simply finding examples of human behavior. If we are able to use human experiences as our main input, we have no problem in learning from them. The challenge arises when trying to learn things about people that we don’t know. Examples of these human behaviors can be found in historical records, literature, art, videos — anything that was available or written by humans. In order to make these data useful for us as models, they need to be labeled, so that we can see what they look like in a visual model. This kind of labeling is known as annotation.
The first attempts at creating “artificial neural networks” were done in 1956 in Dartmouth College by Donald Hebb and Ray Solomon off. They wanted to simulate human brain function using machine learning (ML). Their idea was that the brain would look something like this:
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