Many resources are accessible for free via the Internet; however, the UW library also permits online access to many journals (which would otherwise cost money):
http://www.lib.washington.edu/

Machine Learning Conferences:
http://academic.research.microsoft.com/RankList?entitytype=3&topDomainID=2&subDomainID=6&last=0&start=1&end=100

Machine Learning Journals:
http://academic.research.microsoft.com/RankList?entitytype=4&topDomainID=2&subDomainID=6&last=0&start=1&end=100

Probabilistic Modeling ToolKit:
https://github.com/probml/pmtk3

SciKit Learn:
http://amueller.github.io/
http://scikit-learn.org/stable/auto_examples/

Spark:
https://www.codementor.io/spark/tutorial/

Bayesian Methods:
https://github.com/CamDavidsonPilon/Probabilistic-Programming-and-Bayesian-Methods-for-Hackers

Deep Learning:
http://deeplearning.net/tutorial/
https://github.com/fchollet/keras/tree/master/examples

Spectral Clustering:
http://papers.nips.cc/paper/2092-on-spectral-clustering-analysis-and-an-algorithm

Alternating Least Squares Matrix Factorization:
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.147.8295

Natural Language Processing
http://www.nltk.org/

Latent Dirichlet Allocation:
http://jmlr.org/papers/v3/blei03a.html
http://www.uoguelph.ca/~wdarling/research/papers/TM.pdf

Imbalanced Classification:
https://www3.nd.edu/~dial/publications/chawla2005data.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.131.1506

Graphical Models:
http://ai.stanford.edu/users/koller/papers.cgi?entry=Koller+al:SRL07
http://homepages.inf.ed.ac.uk/csutton/publications/crftut-fnt.pdf

Data:
http://grouplens.org/datasets/movielens/
https://archive.ics.uci.edu/ml/datasets/Reuters-21578+Text+Categorization+Collection
http://www.conll.org/previous-tasks
http://yann.lecun.com/exdb/mnist/
https://www.cs.toronto.edu/~kriz/cifar.html