Bayesian Inference: Error Minimization

This lecture covers the concept of error minimization in Bayesian inference, focusing on the use of least squares to minimize the loss function. It also discusses the calculation of errors and uncertainties in the model, emphasizing the importance of prior knowledge in the inference process.