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Outcome School · ML foundations and math13 min read

by Amit Shekhar · 17 April 2026

Math Behind Gradient Descent

The math behind gradient descent with a step-by-step numeric example.

2,550 words#math#llm#ai#machine-learning4 recall cards

Math Behind Gradient Descent
Read on Outcome School ↗then come back to lock it in
Before you read, guess

What is the primary objective regarding the loss value during the training process?

Ten seconds, a guess, then read — a wrong guess still makes the answer stick.

What this article covers

  1. The Big Picture
  2. What is a Loss Function
  3. What is Gradient Descent
  4. The Intuition Behind Gradient Descent
  5. The Math Behind Gradient Descent
  6. Step-by-Step Numeric Example
  7. Gradient Descent with Multiple Parameters
  8. The Role of Learning Rate
  9. Types of Gradient Descent
  10. Gradient Descent in Python
  11. Putting It All Together

The article lives on outcomeschool.com. Read it there, then come back: the tutor in the margin has read it and will answer questions, and the questions below check what stayed.

Before you go

In one sentence, what was this chapter about?

From memory, without scrolling up. Writing it is what makes it yours; the grade is only to show you what you had.

How sure?