Machine Learning

• EBooks
  • My Colletion
  • bookfi for free ebooks
• Tutorials && Courses
  • General Machine Learning
    • Machine Learning
    • Coursera by Andrew Ng, by Hsuan-Tian Lin fundation and techniques
    • Machine Learning @ CMU by Alex Smola 2013 2015
    • Elements of Statistical Learning @ KTH
    • Advanced Topics in ML 2004, Kernel and Embedding Methods in ML 2005, Beyond Introductory ML 2008
    • Machine Learning Summer School: 2012, 2013, 2014, more
    • 龙星计划(Dragon Star Plan) 2010 2012 2013
    • Scikit-Learn and Python Tutorial
  • Data Mining
    • STATS202 Data Mining @ Stanford
    • Learning From Data
    • Big data CILVR Lab @ NYU
  • Statistical Machine Learning
    • StatLearning 2015 by Trevor Hastie and Robert Tibshirani
    • Statistical Learning @ UCSD I II
  • Large Scale Machine Learning
    • Scalable Machine Learning 2012 @ Berkeley by Alex Smola
    • LSML 2015 @ UToronto by Russ Salakhutdinov
  • Deep Learning
    • A Good Collection
    • Neural networks (NN) by Hugo Larochelle
    • 深度学习 by 吴立德
    • DL and NN 2014 @ Nara Institute of Science and Technology, CIFAR NCAP (Neural Computation & Adaptive Perception) 2014 @ UToronto, Deep learning Feature learning 2014 @ IPAM UCLA
    • DL university
    • Lots of tutorials and workshops in NIPS/ICML/ICML/CVPR/AAAI/I(E)CCV ...
    • Deep learning packages: caffe, theano, cuda-convnet2, cxxnet
• Reviews / PhD Theses: to be added
• Others
  • ArXiv Machine Learning
  • Talking Machines @ SoundCloud
  • Kaggle competition past solutions
  • AMA (ask me anythong) on Reddit by Jordan, Hinton, Lecun, Bengio, ML on Reddit
  • Researchers and Blogs: Andrej Karpathy, FastML, NN and DL by Michael Nielson, Shape of data by Jesse Johnson, Computer Vision for dummies by Vincent Spruyt, Free Mind by pluskid, Probabilistic Graphical Model notes by demonstrate, ML notes by tornadomeet, The elements of statistical learning notes by 落园, ML hunch.net, ML blog technet
  • Bayesian Methods for Hackers
  • Packages: Scikit-Learn, libsvm, list of awesome ml frameworks
  • ReWork-Deep Learning Summits (Gathering of Top Researchers and Geeks) SF Jan 2015, Boston May 2015, London Sep 2015, SF Jan 2016, download brochures by yourself and sniff the frontiers of deep learning both in Academy and Industry.

Computer Vision

• EBooks: Collection
• Tutorials && Courses
  • Introductory
    • UCF Computer Vision 2012 by Mubarak Shah
    • CV 2013 @ WUSTL by Yasutaka Furukawa
  • Advanced / Learning Based with Heavy Machine Learning
    • Mobile Computer Vision 2010 @ UMich, 2014 @ Stanford by Silvio Savarese
    • Advanced Topics in Learning and Vision @ NTU by 楊明玄
    • Special Topics in Computer Vision 2011 @ Cornell by Noah Snavely
    • Advanced Topics in CV 2011 @ Weizmann
    • ML for Robotics and CV 2013 @ TUM
    • Vision Courses @ CMU
    • Special Topics in CV 2010 and Visual Recognition 2012 @ UTexas by Kristen Grauman
    • Advanced Topics in CV 2013 @ VirginiaTech
    • High-Level CV 2014 @ MPI-INF
    • Visual Object and Activity Recognition Seminar @ Berkeley by Trevor Darrell 2014 Fall, 2014 Spring, 2013 Spring, 2012 Spring, 2011 Spring, check how fast research topics changes in recent years
• Reviews / PhD Theses: to be added
• Others
  • ArXiv Computer Vision
  • Computer Vision Papers By Topic, CVonline Compendium
  • The mosted cited papers in CV upto 2012, 20 years of cv by Tomasz Malisiewicz 2015
  • Who is the best at X, ConvNet benchmarks
  • Packages: CCV, VLFeat, RCNN
  • Researchers and Blogs: Ross Girshick, the Serious Computer Vision Blog by Li Yang Ku, tombone's cv blog by Tomasz Malisiewicz, Eric Yuan, bbabenko - lacking capitals, CVChina.info and .net, CV牛人 一, 二

Computer Science Conference Rankings