Phase 2 · Math & Statistics for AI
TopicsChain Rule
Part of the AI Engineer Roadmap.
Summary
The calculus rule for differentiating composed functions — the exact mathematical mechanism behind backpropagation in neural networks.
How to Learn This
- 1Practice the chain rule on nested functions by hand.
- 2Trace a tiny 2-layer neural network's backward pass and identify each chain-rule step.
- 3Understand why backpropagation is 'just' repeated application of the chain rule.
More topics in Math & Statistics for AI
Linear Algebra Basics (Vectors, Matrices)Matrix OperationsEigenvalues & EigenvectorsCalculus Basics (Derivatives, Gradients)Partial DerivativesProbability FundamentalsProbability DistributionsBayes' TheoremDescriptive StatisticsHypothesis TestingCorrelation vs CausationOptimization Basics (Gradient Descent)
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