Module 3 Overview

Theme

Optimization, loss, and regularization

Essential Question

How do we train deep networks reliably when loss surfaces are non-convex and data are noisy?

Module Components

• Book prose: concepts and methods for this module

• Assignment: applied analysis or implementation brief

• Slides: presentation sequence for seminar or lecture delivery

• Narration: spoken version of the slide flow

• Instructor notes: facilitation tips and misconceptions

• Notebook: executable lab aligned with the module theme