Machine Learning for Engineering & Science Applications | IIT Madras - #92 MLE | MAP & Bayesian Regression | Machine Learning for Engineering & Science Applications

Welcome to 'Machine Learning for Engineering & Science Applications' course ! Want to go beyond simple point estimates and embrace the power of probability in your predictions? This lecture delves into the fascinating realm of Bayesian Regression. We'll start by understanding MLE and MAP estimation, two common methods for finding the best-fit parameters for our models. But then, we'll take a leap into Bayesian thinking, where we treat parameters as random variables with their own distributions. By incorporating prior knowledge and updating our beliefs based on data (using likelihood), we'll arrive at the posterior distribution, a richer representation of our model parameters. And the best part? We can generate a full predictive distribution for our output, complete with error bars, giving us a more comprehensive understanding of uncertainties. NPTEL Courses permit certifications that can be used for Course Credits in Indian Universities as per the UGC and AICTE notifications. To understand various certification options for this course, please visit https://nptel.ac.in/courses/106106198 #MLE #MAP #BayesianRegression #GaussianDistribution #PosteriorDistribution #Prior #Likelihood #PredictiveDistribution #PointEstimate #ErrorBar