ocw — open courseware video lectures for machine learning 

Open CourseWare (OCW) refers to publicly available learning resources. OCW started back in 2002 with an initiative brought forward by MIT. Since then many top universities and research institutions started offering high quality learning materials online freely to the public. On this page I'll keep a list of useful OCW resources that I have come across.

Stanford University OCW CS229 Machine Learning Video Lectures by Andrew Ng (Screenshot)

The first online video lectures that I have studied were the MIT 18.06 Linear Algebra lectures by Gilbert Strang, who not only knows the subject but also knows how to convey it very well. It is not difficult to get very interested in the area very quickly. I have also focused my attention on an exciting area of machine learning through Stanford University's CS229 Machine Learning video lectures by Andrew Ng. The lectures are a systematic, from-ground-up, introduction to machine learning. Area specific terminology is introduced and clearly explained. This helps a lot especially when you are getting started. The lectures are well complemented by course notes with detailed derivations and descriptions that aid intuitive understanding. I am also looking forward to studding machine learning lectures by Christopher Bishop, Alex Smola, John Shawe-Taylor and others, available on videolectures.net — yet another fast growing online source of video learning resources.

OK, without further adieu, here are the links succinctly outlined:


Stanford Universitysee.stanford.edu/SEE/courses.aspx


Happy learning! :)

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One Response to “ocw — open courseware video lectures for machine learning”

  1. Jo Says:

    awesome! thx

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