Logistic Regression: The Workhorse of Yes or No ProblemsRemember the Swiggy late-order problem from a couple posts ago? Ten orders, distance in kilometers, and one simple label: was it late, yes or no. We tried fitting our usual straight line to it, and it1Sep 25 · 6 min readtharunpandya.hashnode.dev
The Sigmoid Function: Squashing the World Into 0 and 1You open YouTube. You haven't searched for anything, yet the very first video looks strangely interesting. You click. Imagine a simplified recommendation model working behind the scenes, quietly askin1Sep 19 · 7 min readtharunpandya.hashnode.dev
From Lines to Decisions: Why Regression Fails at ClassificationLast time, right at the end, I asked a question and then walked away from it. Will this order be late, or won't it? The final answer isn't a number on a continuous scale. It's a class: yes or no. Ever1Aug 31 · 9 min readtharunpandya.hashnode.dev
Polynomial Regression: Teaching a Line to BendTake our best straight-line model so far, the one that fit our five-order table perfectly. Now widen the range a bit. Some orders close by, a couple kilometers away. Some far, ten or twelve kilometers1Aug 22 · 10 min readtharunpandya.hashnode.dev
Feature Scaling in Machine Learning: Why It MattersTake the exact same model, the exact same data, the exact same code. Change one thing: write the distance column in meters instead of kilometers. Nothing else moves. Run it, and the model doesn't just1Aug 19 · 10 min readtharunpandya.hashnode.dev
