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Explores statistical tests for independence and homogeneity, including chi-square tests and Fisher's exact test, with practical examples and applications.
Introduces feed-forward networks, covering neural network structure, training, activation functions, and optimization, with applications in forecasting and finance.
Explores Multi-Point Constraints in nonlinear structural analysis, covering methods like Master-Slave Elimination and numerical examples of small frames with enforced constraints.
