Implementing Machine Learning Algorithms

Lecture Notes

This week we continued with the

updated lecture slides from week 4, with a particular focus on continuous probability densities, and how they represent distributions, and then an illustration of how maximum likelihood and minimum error are the same for a Gaussian density and least squares error function.

Learning Outcomes Week 5

This lecture covers the following learning outcomes

  • A review of continuous probability densities.
  • A review of the Gaussian density.
  • The equivalence between least squares and a Gaussian noise approximation.