Machine Learning Laboratory

author: Christfried Webers, NICTA, Australia's ICT Research Centre of Excellence
published: May 7, 2008,   recorded: March 2008,   views: 676
Categories

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.
  Delicious Bibliography

 Watch videos:   (click on thumbnail to launch)

Watch Part 1
Part 1 53:47
!NOW PLAYING
Watch Part 2
Part 2 32:27
!NOW PLAYING
Watch Part 3
Part 3 56:20
!NOW PLAYING

Description

The first laboratory has not been recorded but has featured some hands on experiments with Elefant (http://elefant.developer.nicta.com.au/) mainly concentrating on installing, using, and developing machine learning algorithms within the Elefant framework. We will walk through examples of implementing a simple stochastic gradient descent algorithm as a part of this tutorial. This is the first part of the second session which is split with S.V.N. Vishwanathan's "Machine Learning Laboratory" and will feature hands on experiments with BNRM (Bundle Methods for Regularized Risk Minimization) (http://users.rsise.anu.edu.au/~chteo/BMRM.html). The emphasis here will be on developing various loss function modules which can then be plugged into the BMRM solver.

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment:

make sure you have javascript enabled or clear this field: