Data Mining: Introduction to Linear Regression - Spring 2023
Master linear regression fundamentals, from basic concepts to least squares method, while learning how to apply these techniques for effective data analysis and predictive modeling.
Nonlinear Regression and Regularization in Data Mining - Spring 2023
Master nonlinear regression concepts, from polynomial mappings to regularization techniques, while learning practical implementation in Python and understanding cross-validation for model optimization.
Linear Regression and Parameter Estimation in R - Lecture 17
Master linear regression techniques in R while exploring parameter estimation and random variable estimators through hands-on statistical analysis and practical applications.
Linear Regression and Least Mean Square Method - Lecture 11
Master linear regression fundamentals through least mean square method, loss function minimization, and gradient descent techniques for practical machine learning applications.
Multi-fidelity Linear Regression for Scientific Machine Learning from Scarce Data
Explore multi-fidelity linear regression for scientific machine learning, addressing data scarcity challenges in complex engineering systems through innovative training approaches.
Multivariate Statistical Analysis
Comprehensive exploration of multivariate statistical techniques, covering theory, problem-solving, and implementation in R and Excel. Ideal for data analysis across various fields.
Taming Regression Using APL - From Basic Linear Models to Advanced Applications
Master statistical regression techniques using APL through practical examples, from basic linear models to advanced non-linear and logistic regression, with hands-on demonstrations using TamStat software.