Kernels and Gaussian Processes

Posted in Science on July 28, 2008


Kernels and Gaussian Processes

Lecture slides:

  • Linear Regression
  • Example Prediction Problem
  • Linear Model
  • Loss Functions
  • Squared-Error Loss
  • Matrix Notation
  • Minimising MSE
  • Stationary Point
  • Least Squares Solution
  • Prediction
  • Nonlinear Model
  • Probabilistic Regression
  • Noise Distribution
  • Maximum Likelihood
  • Estimate Uncertainty
  • Likelihood

Author: Mark Grolami, University of Glasgow

Watch Video

Tags: Science, Lectures, Computer Science, Machine Learning, VideoLectures.Net, Gaussian Processes, Kernel Methods