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 25, 2026·1 min read

PCA Doesn't Remove Features: It Finds Better Ones

When you have a dataset with 50 features, most ML models struggle. More features means more noise, slower training, and harder interpretation. The naive solutio

June 24, 2026·1 min read

Clustering Without Labels: K-Means, Hierarchical, and How They See the World Differently

Everything up to now has been supervised: models that learn from labeled data. Today I hit the first unsupervised algorithms: clustering. The task is to find gr

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