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Calculus for Gradient Descent
Learning Objectives
- •Derivatives as a measure of change
- •Partial Derivatives and Gradients for multivariate functions
- •The Chain Rule: The core of backpropagation
- •Understanding the Gradient Descent optimization algorithm
Weekly Outcome
By the end of this module you will be able to explain and implement the core mathematical concepts required for backpropagation, including multivariate calculus (gradients, chain rule) and basic linear algebra.
Resources
ML Foundations: Understanding the Math Behind BackpropagationBackpropagation Math + Intuition - YouTubery-ops | Understanding Neural Network Backpropagation: The ...Backpropagation: Step-By-Step Derivation - Towards Data ScienceUnderstanding Backpropagation: The Engine Behind Neural ...Backpropagation in Neural Network - GeeksforGeeksUnderstanding Backpropagation: The Math Behind Neural Netsry-ops | Understanding Neural Network Backpropagation: The ...