Prototyping with SP80 - MAKE project

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Related lectures (32)

Page 3 of 4

Explores polynomial curve fitting, kernel functions, and regularization techniques, emphasizing the importance of model complexity and overfitting.

Polynomial Regression: Basics and Regularization

Covers the basics of polynomial regression and regularization to prevent overfitting.

Regression Trees and Ensemble Methods in Machine Learning

Discusses regression trees, ensemble methods, and their applications in predicting used car prices and stock returns.

Metrics for Classification

Covers sampling, cross-validation, quantifying performance, optimal model determination, overfitting detection, and classification sensitivity.

Hydroacoustics for Hydroelectric Installations

Explores valve closing laws, water hammer, and surge tanks in hydroelectric installations.

Using cross-validation: Building a final predictor

Covers the interpretation of cross-validation risk estimates and building a final predictor from cross-validation results.

Model Selection: Non-Nested Model Selection

Explores model selection, criteria, bias/variance tradeoff, and cross-validation methods.

Model Evaluation and Selection

Discusses model evaluation, cross-validation, and variable selection in machine learning.

Validated-Aware Software

Explores validated-aware software for continuous system validation in safety-critical environments, emphasizing the importance of anticipatory real-time assurance and semantic-level validation.

Supervised Learning in Financial Econometrics

Explores supervised learning in financial econometrics, covering linear regression, model fitting, potential problems, basis functions, subset selection, cross-validation, regularization, and random forests.