Mediaspace scheduled maintenance: Aug 25, 2026 07:00 - 12:00 AM. During this time, videos will be temporarily unavailable. Check status updates.

Home

Lecture

Advanced Machine Learning: Ridge Regression

About
Privacy
Disclaimer

Graph Chatbot

Related lectures (51)

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.

Regression: Interactive Lecture Log in to Mediaspace to watch this video

Covers linear regression, weighted regression, locally weighted regression, support vector regression, noise handling, and eye mapping using SVR.

Linear Regression: Regularization Log in to Mediaspace to watch this video

Covers linear regression, regularization, and probabilistic models in generating labels.

Linear Regression Basics Log in to Mediaspace to watch this video

Covers the basics of linear regression, instrumental variables, heteroskedasticity, autocorrelation, and Maximum Likelihood Estimation.

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

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

Linear Regression: Basics and Estimation Log in to Mediaspace to watch this video

Covers the basics of linear regression and how to solve estimation problems using least squares and matrix notation.

Feature Engineering: Polynomial Regression Log in to Mediaspace to watch this video

Covers fitting linear regression on features of the original predictors for flexible feature representation.

Regression: High Dimensions Log in to Mediaspace to watch this video

Explores linear regression in high dimensions and practical house price prediction from a dataset.

Linear Regression: Parametric Models and Optimization Log in to Mediaspace to watch this video

Covers linear regression, parametric models, optimization, and predictive modeling using labeled examples.

Polynomial Regression: Basics and Regularization Log in to Mediaspace to watch this video

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

Data-Driven Modeling: Regression Log in to Mediaspace to watch this video

Introduces data-driven modeling with a focus on regression, covering linear regression, risks of inductive reasoning, PCA, and ridge regression.

Basics of linear regression model Log in to Mediaspace to watch this video

Covers the basics of linear regression, OLS method, predicted values, residuals, matrix notation, goodness-of-fit, hypothesis testing, and confidence intervals.

Applied Biostatistics: Bivariate Data Analysis Log in to Mediaspace to watch this video

Explores bivariate data analysis in applied biostatistics, covering correlation, regression, model selection, and diagnostics.

Linear Regression: Regularization Overview Log in to Mediaspace to watch this video

Explores linear regression fundamentals, emphasizing the importance of regularization techniques to enhance model performance.

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.

Introduction to OLS Log in to Mediaspace to watch this video

Covers the basics of Ordinary Least Squares (OLS) in econometrics, including variable relationships, coefficient determination, and model interpretation.

Machine Learning in Molecular Dynamics Log in to Mediaspace to watch this video

Explores the application of machine learning in molecular dynamics and materials, emphasizing the creation of meaningful features and the importance of generalizability.

Linear Regression: Multicollinearity, Outliers, Model Specification Log in to Mediaspace to watch this video

Covers multicollinearity, outliers, model specification, and practical strategies in linear regression.

Supervised Learning Fundamentals Log in to Mediaspace to watch this video

Introduces the fundamentals of supervised learning, including loss functions and probability distributions.

Machine Learning for Atomic Scale Systems Log in to Mediaspace to watch this video

Explores applying machine learning to atomic scale systems, emphasizing symmetry in feature mapping and the construction of rotationally invariant descriptors.

Page 2 of 3