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Use this to learn at degree level how convolutional neural networks are used for visual recognition 

Step-by-step guide

  1. prereq CS229 Machine learning ML, formulating cost fn, taking derivatives,
    performing optimisation w/ gradient descent

  2. prereq CS109 basic probability and stats
  3. get PDF slides and video mpeg4 URLS from  http://cs231n.stanford.edu/slides/2017/
  4. http://cs231n.github.io/    includes assignments
  5. demos http://vision.stanford.edu/teaching/cs231n-demos/linear-classify/

 

you should know basic math : linear algebra, partial derivatives, integration etc


silvestro courses
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http://web.stanford.edu/class/cs231m/spring-2014/papers.html
http://web.stanford.edu/class/cs231a/course_notes.html
https://github.com/kenjihata/cs231a-notes




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