Discussing the article: "Neural Networks in Practice: An Example of Implementing an XOR Gate"

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Check out the new article: Neural Networks in Practice: An Example of Implementing an XOR Gate.

In this article, I will try to show you, dear reader, that things are not always what they seem. We often tend to think that everything is arranged in a certain way, even though we may end up believing something that isn't necessarily true. Neural networks are undoubtedly one of the most interesting topics, whether viewed from the perspectives of mathematics, electronics, or software. Contrary to what many people believe or claim, neural networks are neither a problem nor a definitive solution. This is just one area of research where we should continue to delve deeper and explore what goes on behind the scenes.

In my previous article, “Neural Networks in Practice: Practice Makes Perfect”, I explained how to speed up computations or the adjustment of values within a simple neuron. And all of this is part of what I'm currently developing; I'll show you later how to implement it. I have absolutely no intention of showing you here how to create a neural network intended for attempts at trading in the financial market. The goal is to explain as clearly and vividly as possible how a neural network is trained and, most importantly, how it works behind the scenes.

In that same article, I included a small table, which you can see below:

This small table, also known as a truth table, shows readers researching this topic or studying electronics how a circuit responds to the data fed into its inputs. In other words, by looking at this table, we can understand how an electronic device will work. Essentially, this shows the configurations of the basic logic gates that can be implemented. From left to right, we have the logic gates AND, NAND, OR, NOR, XOR, and XNOR.

Author: Daniel Jose