Neural Networks: Multilayer PerceptronsCovers Multilayer Perceptrons, artificial neurons, activation functions, matrix notation, flexibility, regularization, regression, and classification tasks.
Probabilistic Linear RegressionExplores probabilistic linear regression, covering joint and conditional probability, ridge regression, and overfitting mitigation.
Back to Linear RegressionCovers linear regression, regularization, inverse problems, X-ray tomography, image reconstruction, data inference, and detector intensity.
Regression: Linear ModelsExplores linear regression, least squares, residuals, and confidence intervals in regression models.
