Week 2: Objective Functions: A Simple Example with Matrix Factorization

Lecture Notes

Objective Functions

Lab Class

The notebook for the lab class can be downloaded from here.

To obtain the lab class in ipython notebook, first open the ipython notebook. Then paste the following code into the ipython notebook

import urllib
urllib.urlretrieve('https://raw.githubusercontent.com/SheffieldML/notebook/master/lab_classes/machine_learning/week2.ipynb', 'week2.ipynb')

You should now be able to find the lab class by clicking File->Open on the ipython notebook menu.

Additional Material

• The $1 Million Netflix Prize

Learning Outcomes Week 2

• Understand what an objective function is.
• Understand the basic principles of collaborative filtering by matrix factorization.
• Understand the idea of knowledge representation in terms of vector data.
• Understand a simple iterative optimizer such as a gradient methods.
• Understand the difference between steepest descent and stochastic gradient descent.
• Understand the use of momentum in the gradient descent algorithm.

This document last modified Wednesday, 08-Oct-2014 09:35:16 UTC