Gradient Descent: A Beginner-Friendly Guide to How Models Learn
Most modern ML models—from simple regressions to deep neural networks—learn using the core idea i.e. Gradient Descent. It’s an optimization method that adjusts model parameters gradually to minimize the error, very similar to like walking downhill till you reach the lowest point of a hill. Rolling ball down the hill – An analogy Imagine this…
