

Links to Stanford Machine Learning lectures, login not required - zeratul

I'm sure you all know about www.ml-class.org - if I were to distillate all lectures to bare minimum it would be to learn about support vector machines (SVM).<p>Contrary to common believes SVMs are a VERY large class of learners. Linear SVM would be just 1 of 10^10 ways of using SVM. It can be used to do regression, classification, clustering, feature selection, feature weighting, feature engineering, projections, and visualizations. That's why I decided to post few links to the prof. Ng's videos (in the comments section to have clickable URLs).
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zeratul
Ones, that I would focus on:

Model selection [http://www.ml-
class.org/course/video/embed?video_id=62&s...](http://www.ml-
class.org/course/video/embed?video_id=62&speed=100&seekTo=0)

Diagnosing bias vs. variance [http://www.ml-
class.org/course/video/embed?video_id=63&s...](http://www.ml-
class.org/course/video/embed?video_id=63&speed=100&seekTo=0)

SVM Optimization Objective [http://www.ml-
class.org/course/video/embed?video_id=72&s...](http://www.ml-
class.org/course/video/embed?video_id=72&speed=100&seekTo=0)

Large Margin Intuition [http://www.ml-
class.org/course/video/embed?video_id=73&s...](http://www.ml-
class.org/course/video/embed?video_id=73&speed=100&seekTo=0)

Mathematics Behind Large Margin Classification (Obligatory!!!) [http://www.ml-
class.org/course/video/embed?video_id=74&s...](http://www.ml-
class.org/course/video/embed?video_id=74&speed=100&seekTo=0)

Kernels I [http://www.ml-
class.org/course/video/embed?video_id=75&s...](http://www.ml-
class.org/course/video/embed?video_id=75&speed=100&seekTo=0)

Kernels II [http://www.ml-
class.org/course/video/embed?video_id=76&s...](http://www.ml-
class.org/course/video/embed?video_id=76&speed=100&seekTo=0)

Using An SVM [http://www.ml-
class.org/course/video/embed?video_id=77&s...](http://www.ml-
class.org/course/video/embed?video_id=77&speed=100&seekTo=0)

... yep, you don't need to login.

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Edmond
I would like to recommend HoloKlip (<http://bit.ly/uoOuRh>) for managing video
lessons. Instead of multiple clips and urls, you just virtually clip one
video.

