why & what

The why

I began hearing the term "artificial intelligence" more frequently in early 2022, which piqued my curiosity: What does "artificial intelligence" actually mean? Are machines or computers magically "thinking" like humans do?

My investigations revealed that "artificial intelligence" was just the tip of the iceberg, concealing a world of familiar concepts: statistics, probabilities, and linear algebra. This realization was enough to inspire me to dive into the topic and get hands-on experience.

As my learning journey progressed, Python became a steadfast companion. Throughout my career, I had learned languages like Turbo Pascal, Delphi, C++, and extensively used VBA professionally, but I had never explored Python—what a missed opportunity! Python's initial steps can be taken quickly; the language is easy to read and offers great flexibility when working with objects and iterables. Moreover, it's widely used in machine learning and deep learning, to orchestrate calculations performed with dedicated libraries such as NumPy or PyTorch.

The what

Here, you'll find articles presenting concepts and techniques related to mathematics, machine learning, and deep learning, all illustrated with Python. These articles will cover ideas and topics I found intriguing during my learning journey, which I hope others might enjoy as well.

The purpose is to showcase situations where these concepts and techniques can add value to processes and analytics compared to more standard approaches.

You won't find PhD-level discussions here (for those, you might try your luck at https://arxiv.org/ :) ).