Sharing notes from my ongoing learning journey — what I build, break and understand along the way.
Understanding Transformers: The Architecture Behind Modern AI Models A few years ago, if you wanted a machine to understand text, you had to feed it information word by word, like reading a sentence to a child very slowly and hoping…
AI, ML, and DL Explained Simply: What They Are and How They Connect If you’re into technology, chances are you’ve seen these three acronyms a lot: AI, ML, and DL. They pop up in conferences, LinkedIn posts, and even when…
Linear Regression and the Cost Function: Step-by-Step Guide with Calculations As someone who is just beginning to explore the field of artificial intelligence, I’ve realized that it’s not enough to focus solely on large models — I also need to…
What Is Reinforcement Learning? A Beginner-Friendly Explanation with Examples In some machine learning problems, we don’t have the correct answer in advance, nor even labeled data. Instead, the model must learn from experience by trying, observing outcomes, and improving over…
Unsupervised Learning: How Machines Learn Without Labels In this section, I want to explore how we can build models even when we have no labeled data at all. This brings us to unsupervised learning—a set of techniques used when there’s…
Supervised Learning Explained: Regression and Classification for Beginners I’m currently taking a machine learning course on Coursera, and one of the first major topics covered is Supervised Learning. To solidify what I’ve learned and also share helpful content on my…