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

July 4, 2026·2 min read

Gradient Descent Doesn't Know Where the Minimum Is: It Only Knows Which Way Is Down

Backpropagation tells you the gradient: how much each weight should change to reduce the cost. Gradient Descent is the algorithm that actually uses that gradien

June 29, 2026·2 min read

Feature Selection Picks What to Keep, Feature Extraction Builds Something New

Not all features in a dataset are worth keeping. Some are redundant. Some are noise. Some slow down training without adding any predictive signal. Feature engin

June 28, 2026·2 min read

Ridge Shrinks Coefficients, Lasso Zeros Them Out: Why That Difference Matters

Regularization is not about making your model more accurate on training data. It is about making it less wrong on data it has never seen. When a model fits too