My ML Journey

Why I'm Documenting This

Learning ML in public. Every entry is a day of studying: what clicked, what confused me, and what I'm pulling on next. Writing forces me to actually understand things, not just watch them go by. If it helps someone else figure something out, even better.

Daily notes on machine learning, deep learning, and AI.

3 entries

June 26, 2026·1 min read

MSE Penalizes Big Mistakes Harder: R² Tells You If Your Model Even Learned Anything

You've trained a regression model. It outputs numbers. How do you know if those numbers are any good? Two metrics cover this from different angles: MSE measures

June 18, 2026·1 min read

Linear Regression Is Just Finding the Best Straight Line: Here's What That Actually Means

Linear regression is the first algorithm most people learn and often the most underestimated. At its core, it does one thing: fits a straight line through data

June 17, 2026·1 min read

The Map Before the Territory: How ML Splits Into Supervised and Unsupervised

Before you can understand any specific ML algorithm, you need to understand why ML splits into two completely different philosophies, and what that distinction