juanspinelli / courses

Programming solutions for some courses

• cs231: CS231n Convolutional Neural Networks for Visual Recognition (Stanford)
• gpucuda: Intro to parallel programming with CUDA (finished, didn't do some tedious exercises)
• noc: Nature of Code (barely started)
• jurlia: Reinforcement Learning (barely started)
• ndata: Exploring Neural Data, Coursera/Brown, 2014 (all except last assignment, not available anymore)
• mlsclassng: Machine Learning, Andrew NG, coursera 2014 (finished)
• pgm: Probabilistic Graphical Models, (finished)
• ipim: Code for Introduction to Medical Image Processing course, UBA, 2014 (finished)

PGM links

http://www.cs.cmu.edu/~epxing/Class/10708/hw/pgm_2014_homework1_sol.pdf http://cs.nyu.edu/~dsontag/courses/pgm13/ http://www.cs.cmu.edu/~epxing/Class/10708/lecture.html http://courses.cms.caltech.edu/cs155/ http://www.cedar.buffalo.edu/~srihari/CSE574/ http://openclassroom.stanford.edu/MainFolder/CoursePage.php?course=ProbabilisticGraphicalModels https://www.youtube.com/playlist?list=PL50E6E80E8525B59C crfs tutorial

DL links

https://github.com/DeepLearningDTU/nvidia_deep_learning_summercamp_2016

https://github.com/DeepLearningDTU/02456-deep-learning