Module
Calculus and Gradients for Optimization
Sign in to add this module to your path and practice.
About
Partial derivatives, gradients, chain rule, and simple multivariable optimization—enough to derive gradient descent updates for common losses.
Goal
Compute gradients of squared error and cross-entropy (with sigmoid/softmax), and write a basic gradient-descent step from first principles.
Unlocks
Tutor
Ask questions about this module.
Hi — I'm your tutor for Calculus and Gradients for Optimization. Ask about the concepts, goal, or where you're stuck.