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Related lectures (30)

Supervised Learning Essentials Log in to Mediaspace to watch this video

Introduces the basics of supervised learning, focusing on logistic regression, linear classification, and likelihood maximization.

Diagnostic Tests: Sensitivity and Specificity Log in to Mediaspace to watch this video

Explains Sensitivity, Specificity, ROC curve, and Precision in diagnostic tests.

Linear Models: Basics Log in to Mediaspace to watch this video

Introduces linear models in machine learning, covering basics, parametric models, multi-output regression, and evaluation metrics.

Polynomial Regression: Overview Log in to Mediaspace to watch this video

Covers polynomial regression, flexibility impact, and underfitting vs overfitting.

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

Covers the basics of linear regression, binary and multi-class classification, and evaluation metrics.

Model Selection: Evaluation and Generalization Log in to Mediaspace to watch this video

Explores model selection, evaluation, and generalization in machine learning, emphasizing unbiased performance estimation and the risks of over-learning.

Laplace Transform: Basics Log in to Mediaspace to watch this video

Introduces Laplace transform, ROC, and LTI systems with transfer functions and frequency response.

Powder Treatment: Milling and Classification Log in to Mediaspace to watch this video

Explores powder treatment through milling and classification techniques for ceramic production, covering crushing, milling, particle breakage, and powder synthesis.

Genome-wide Association Studies: Statistical Analysis Log in to Mediaspace to watch this video

Explains the statistical analysis of Genome-wide Association Studies and the importance of adjusting for multiple testing.

Linear Models for Classification: Multi-Class Extensions Log in to Mediaspace to watch this video

Covers linear models for multi-class classification, focusing on logistic regression and evaluation metrics.

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