Decision theory

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Decision Theory: Risk and Hypothesis Testing

Covers decision theory, risk functions, and hypothesis testing in statistical inference.

Bayesian Decision Theory: Utility, Risk, and Classification

Covers Bayesian decision theory, cost functions, classification, and decision rules.

SAT Solver: Optimization Techniques

Explores optimization techniques in SAT solvers and their application in Sudoku solving.

Detection & Estimation

Covers binary classification, hypothesis testing, likelihood ratio tests, and decision rules.

Factored Representations: Planning Efficiency

Explores factored representations for planning, focusing on reducing complexity and improving efficiency through separate feature modeling.

Introduction to Convexity

Introduces the key concepts of convexity and its applications in different fields.

Boolean Satisfiability Problem: Solving Techniques

Explores the Boolean Satisfiability Problem and the Davis-Putnam-Logemann-Loveland algorithm, along with modern SAT solvers and efficient solving techniques.

Maximum Likelihood Estimation

Covers Maximum Likelihood Estimation, focusing on ML Estimation-Distribution, Shrinkage Estimation, and Loss functions.

Decision Tree Classification

Covers decision tree classification using KNIME Analytics Platform for data preprocessing and model creation.

Sexing Guppy Fish: Bayesian Inference and Decision Rules

Covers the sexing of guppy fish using Bayesian inference and decision rules.