Over the past several years, there has been much excitement around artificial intelligence and neural networks. These technologies have powered a variety of new technologies from voice commanded automation to self-driving cars. In fact Forbes has states that advancements in AI will amount to 38% of economic growth by 2035.
In order to better understand neural networks, we have to delve into it's lineage of algorithms and what they are trying to achieve. Only then can we see and understand what it is and what it isn't. All this stems from something that humans already do - we learn from experiences in order to draw conclusions on new data, whether that is to classify things or to predict what is likely to happen in the future.
In most secondary education systems, students are taught about trend lines. In order to take a set of points and use them to create a trend we use a form of polynomial regression.