In recent years, artificial intelligence has become almost everywhere: it recognizes our faces on smartphone cameras, translates text from foreign languages, and can even draw pictures or write stories. One of the engines behind these impressive developments is the neural network..

But what exactly is a neural network? And what does it have to do with our brain?

A Simple Analogy

Imagine a tiny decision-maker: a "neuron" that looks at a single input (e.g., temperature) and, based on a simple rule, decides whether to answer “yes” or “no.” If we connect many of these small decision-makers, they can solve more complex problems together. This basic idea is at the heart of artificial neural networks.

What is an Artificial Neuro

An artificial neuron is a simplified mathematical model of the brain’s nerve cells (neurons).  

A biological neuron receives inputs from other cells, processes the information, and decides whether to pass on the signal.

Similarly, an artificial neuron :

• receives multiple input values ,  
• multiplies them by weights, which determine how important each input is,  
• adds a bias value, which acts as a baseline adjustment,  
• and then transforms the result using an activation function , before sending it forward to the next layer.  

In short: weights determine the importance of inputs, while bias fine-tunes the decision.

Why are Neural Networks Important?

• Image recognition: when Facebook automatically tags people in photos.  
• Translation: when Google Translate translates entire sentences, not just words.  
• Chatbots: when a virtual customer service assistant appears on a website.

They can do all this because neural networks are extremely good at recognizing patterns in data.

What Will This Series Cover?

In this series, I will try to show you step by step:  

1. What an artificial neuron is, and how to describe it in Python.  
2. How a simple network is built from multiple neurons.  
3. What a loss functionis, and why it matters.  
4. How a network learns (backpropagation).  
5. How we can use them for real-world problems.  

I strive to write in plain language in my articles, avoiding very dry, technical text and complicated mathematical formulas. I will only write about the mathematics behind how things work, as much as is absolutely necessary for understanding.

In this series, I will program a simple neural network from scratch with all its features. I will use the Python language for this.

You might ask, what's the point of programming a neural network from scratch when there are ready-to-use frameworks where you can build any network with a few lines of code? Well, I think it's because it's exciting to look a little "behind the scenes" and understand how things work. And because it's fun!

Next Article

In the next article, we’ll take a closer look at how an artificial neuron works, and write our first Python code which demonstrates this in practice.