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Related lectures (32)

Machine Learning in Credit Risk Modeling

Delves into the challenges and opportunities of machine learning in credit risk modeling, comparing traditional statistical models with machine learning methods.

Gaussian Mixture Regression: Theory and Applications Log in to Mediaspace to watch this video

Explores Gaussian mixture regression and overfitting with multiple Gauss functions.

Machine Learning at the Atomic Scale Log in to Mediaspace to watch this video

Explores simple models, electronic structure evaluation, and machine learning at the atomic scale.

Decentralized Optimization Log in to Mediaspace to watch this video

Explores decentralized optimization in machine learning, emphasizing robustness, privacy, and fairness in collaborative learning.

Do ImageNet Classifiers Generalize?Log in to Mediaspace to watch this video

Examines the generalization of ImageNet classifiers, safety-critical applications, overfitting, and the reliability of machine learning models.

Data Representation: BoW and Imbalanced Data Log in to Mediaspace to watch this video

Covers overfitting, model selection, validation, cross-validation, regularization, kernel regression, and data representation challenges.

Improving Density Predictions in Machine Learning Log in to Mediaspace to watch this video

Explores enhancing machine learning predictions by refining error metrics and applying constraints for improved accuracy in electron density predictions.

Gaussian Naive Bayes & K-NN Log in to Mediaspace to watch this video

Covers Gaussian Naive Bayes, K-nearest neighbors, and hyperparameter tuning in machine learning.

Image Classification: Decision Trees & Random Forests Log in to Mediaspace to watch this video

Explores image classification using decision trees and random forests to reduce variance and improve model robustness.

Machine Learning Fundamentals: Overfitting and Regularization Log in to Mediaspace to watch this video

Covers overfitting, regularization, and cross-validation in machine learning, exploring polynomial curve fitting, feature expansion, kernel functions, and model selection.

Understanding ImageNet Classifiers Log in to Mediaspace to watch this video

Explores the generalization of ImageNet classifiers and the challenges in achieving reliable machine learning models.

Regression: Exercises Log in to Mediaspace to watch this video

Covers exercises on regression functions using RLS, WLS, and LWR.

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