Decision analysis

Related lectures (32)

Page 3 of 4

Explores optimization in energy system modeling, covering decision variables, objective functions, and different strategies with their pros and cons.

Delves into ethics and law in AI, focusing on values, normative ambitions, and ethical challenges.

Covers the basics of compilation and C++ programming, including variables, functions, loops, and debugging.

Explores the extension of linear classifiers to handle multiclass problems and compares their performance on various datasets.

Covers the basics of support vector machines, logistic regression, decision boundaries, and the k-Nearest Neighbors algorithm.

Explores decision-making processes, including weighing costs and benefits, cues following, and the limitations of cost-benefit analysis.

Explores venture financing stages, funding analysis, sources, and burn rate importance.

Explores signed distance, perceptron, logistic regression, cross entropy, and multi-class classification.

Covers linear models, logistic regression, decision boundaries, k-NN, and practical applications in authorship attribution and image data analysis.

Explores decision trees, overfitting elimination, boosting techniques, and their practical applications in predictive modeling.