Math & statistics
Optimization Methods
5 self-contained study topics — notes, diagrams, formulas, and worked examples for exams and GATE.
Topics
- Unconstrained OptimizationFor B.Tech exams, unconstrained optimization is tested for definition plus one direct derivation or numerical; align notation with Tan, Steinbach & Kumar (Introduction to Data Mining).
- Constrained OptimizationFor B.Tech exams, constrained optimization is tested for definition plus one direct derivation or numerical; align notation with Tom Mitchell (Machine Learning).
- Gradient Descent MethodsFor B.Tech exams, gradient descent methods is tested for definition plus one direct derivation or numerical; align notation with Bishop (Pattern Recognition and Machine Learning).
- Convex Optimization BasicsFor B.Tech exams, convex optimization basics is tested for definition plus one direct derivation or numerical; align notation with Goodfellow, Bengio & Courville (Deep Learning).
- Lagrange MultipliersFor B.Tech exams, lagrange multipliers is tested for definition plus one direct derivation or numerical; align notation with Tan, Steinbach & Kumar (Introduction to Data Mining).