Practical Aspects of Gaussian Linear Model

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Model Building: Linear Regression

Explores model building in linear regression, covering techniques like stepwise regression and ridge regression to address multicollinearity.

Ridge Regression: Penalised Least Squares

Explores Ridge Regression for handling multicollinearity and the LASSO method for model selection.

Model Selection Criteria: AIC, BIC, Cp

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Kernel Methods: Machine Learning

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Overfitting, Cross-validation & Regularization

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LASSO Regression: Sparse Signal Induction

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Geometry of the Lasso

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Specification Testing and Machine Learning

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Probabilistic Linear Regression

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Overfitting in Supervised Learning: Case Studies and Techniques Log in to Mediaspace to watch this video

Addresses overfitting in supervised learning through polynomial regression case studies and model selection techniques.

Sparse Regression Log in to Mediaspace to watch this video

Covers the concept of sparse regression and the use of Gaussian additive noise in the context of MAP estimator and regularization.

Regularization in Machine Learning Log in to Mediaspace to watch this video

Introduces regularization techniques to prevent overfitting in machine learning models.

Machine Learning Fundamentals: Regularization and Cross-validation Log in to Mediaspace to watch this video

Explores overfitting, regularization, and cross-validation in machine learning, emphasizing the importance of feature expansion and kernel methods.

Supervised Learning in Financial Econometrics Log in to Mediaspace to watch this video

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Supervised Learning: Regression Methods Log in to Mediaspace to watch this video

Explores supervised learning with a focus on regression methods, including model fitting, regularization, model selection, and performance evaluation.

Cross-validation & Regularization Log in to Mediaspace to watch this video

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Linear Regression and Logistic Regression Log in to Mediaspace to watch this video

Covers linear and logistic regression for regression and classification tasks, focusing on loss functions and model training.

Cross-Validation: Techniques and Applications Log in to Mediaspace to watch this video

Explores cross-validation, overfitting, regularization, and regression techniques in machine learning.

Regularization Techniques Log in to Mediaspace to watch this video

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