Introduction To Machine Learning (Smola & Vishwanathan)(alex.smola.org)
alex.smola.org
Introduction To Machine Learning (Smola & Vishwanathan)
http://alex.smola.org/drafts/thebook.pdf
2 comments
Also note that this book is not for the faint of heart.
For introductory material you may want to take a look at some of these courses:
Shalizi, 35-350: http://www.stat.cmu.edu/~cshalizi/350/
Shalizi, 36-402: http://www.stat.cmu.edu/~cshalizi/402/
Ng, CS229: http://www.stanford.edu/class/cs229/materials.html
Ng, CS294: http://www.stanford.edu/class/cs294a/
Roth, CS446: http://l2r.cs.uiuc.edu/~danr/Teaching/CS446-10/lectures.html
Jebara, COMS4771: http://www.cs.columbia.edu/~jebara/4771/handouts.html
Jebara, COMS6772: http://www.cs.columbia.edu/~jebara/6772/solutions.html
Jordan, CS294: http://www.cs.berkeley.edu/~jordan/courses/294-fall09/
Kumar, EECS6898: http://www.sanjivk.com/EECS6898/lectures.html
Collins, COMS6998: http://www.cs.columbia.edu/~mcollins/courses/e6998-3/index.h...
Jaakkola & Collins, 6.867: http://courses.csail.mit.edu/6.867/lectures.html
Hamilton, CS831: http://www2.cs.uregina.ca/~hamilton/courses/831/
Girolami, MLM: http://www.dcs.gla.ac.uk/~girolami/Machine_Learning_Module_2...
Bengio, IC-49: http://bengio.abracadoudou.com/lectures/
Lin, CMSC838: http://www.umiacs.umd.edu/~jimmylin/cloud-2010-Spring/syllab...
For introductory material you may want to take a look at some of these courses:
Shalizi, 35-350: http://www.stat.cmu.edu/~cshalizi/350/
Shalizi, 36-402: http://www.stat.cmu.edu/~cshalizi/402/
Ng, CS229: http://www.stanford.edu/class/cs229/materials.html
Ng, CS294: http://www.stanford.edu/class/cs294a/
Roth, CS446: http://l2r.cs.uiuc.edu/~danr/Teaching/CS446-10/lectures.html
Jebara, COMS4771: http://www.cs.columbia.edu/~jebara/4771/handouts.html
Jebara, COMS6772: http://www.cs.columbia.edu/~jebara/6772/solutions.html
Jordan, CS294: http://www.cs.berkeley.edu/~jordan/courses/294-fall09/
Kumar, EECS6898: http://www.sanjivk.com/EECS6898/lectures.html
Collins, COMS6998: http://www.cs.columbia.edu/~mcollins/courses/e6998-3/index.h...
Jaakkola & Collins, 6.867: http://courses.csail.mit.edu/6.867/lectures.html
Hamilton, CS831: http://www2.cs.uregina.ca/~hamilton/courses/831/
Girolami, MLM: http://www.dcs.gla.ac.uk/~girolami/Machine_Learning_Module_2...
Bengio, IC-49: http://bengio.abracadoudou.com/lectures/
Lin, CMSC838: http://www.umiacs.umd.edu/~jimmylin/cloud-2010-Spring/syllab...
Thank you very much for these resources.
I've found Andrew Ng's notes to be very comprehensive and very relevant to the topics discussed in his online lectures : http://academicearth.org/courses/machine-learning (the notes are linked to on the individual videos)
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There is a course by one of the authors with good lecture notes: http://www.stat.purdue.edu/~vishy/introml/introml.html