A snapshot of my journey exploring machine learning and AI systems — through code, experiments, and reflection.
Each folder captures a point in time when I tried to understand a concept by building something around it — sometimes a small experiment, sometimes a comparison, sometimes just a question I needed to reason through.
These notes aren’t comprehensive or definitive. They’re traces of curiosity — an engineer’s attempt to make sense of ideas that connect modeling, systems, and reasoning.
Topics range from classical ML and statistics to modern MLOps, GenAI agents, retrieval pipelines, and evaluation frameworks. The collection isn’t a guide; it’s a record of what I’ve explored, what I’ve learned, and how my understanding evolved.