Author name: Manish Patil

ai, loss, Machine Learning, probability, statistics

From Probability to Loss – How MLE Builds Machine Learning: Part 2

Manish Patil / March 22, 2026

A quick recap of where we left offIn Part 1, we followed a single thread of logic from start to finish.Read: From Probability to Loss — How MLE Builds Machine Learning: Part 1We started with a question: Given data, how do we find parameters that make s…

Artificial Intelligence, Machine Learning, maximum-likelihood, probability, statistics

From Probability to Loss — How MLE Builds Machine Learning: Part 1

Manish Patil / March 20, 2026

Loss functions aren’t magic. They aren’t some arbitrary design choice that researchers pulled out of thin air. Every loss function you’ve ever seen has a story, a logical, step-by-step derivation rooted in probability theory. By the end of this piece, …