This is a small subset of a vast reference published by Eren Golge. I've selected what I believe to be of interest to many of us, but the initial list is far bigger.

Source: MIT (credit risk models based on machine learning)

Introduction to Machine Learning

• http://homepages.inf.ed.ac.uk/rbf/IAPR/researchers/MLPAGES/mltut.htm
• http://jeremykun.com/2012/08/04/machine-learning-introduction/
• http://www.omidrouhani.com/research/machinelearning/html/machinelea...
• https://www.youtube.com/playlist?list=PLD63A284B7615313A (cal tech class)

Support Vector Machines

• http://www.cs.ucf.edu/courses/cap6412/fall2009/papers/Berwick2003.pdf
• http://www.cs.columbia.edu/~kathy/cs4701/documents/jason_svm_tutori...
• https://www.youtube.com/watch?v=eHsErlPJWUU
• http://web.mit.edu/zoya/www/SVM.pdf

 Clustering

• http://en.wikipedia.org/wiki/Cluster_analysis
• http://en.wikipedia.org/wiki/K-means_clustering
• https://www.youtube.com/watch?v=0MQEt10e4NM&feature=c4-overview...

Dimensionality Reduction

• http://en.wikipedia.org/wiki/Dimensionality_reduction
• http://research.cs.tamu.edu/prism/lectures/iss/iss_l10.pdf
• http://www.math.uwaterloo.ca/~aghodsib/courses/f06stat890/readings/...
• https://www.youtube.com/watch?v=EHIZ7Pk1XVY
• https://www.youtube.com/watch?v=mz618Tesra4

 Anomaly Detection

• www.siam.org/meetings/sdm08/TS2.ppt
• http://en.wikipedia.org/wiki/Anomaly_detection

Recommender Systems

• http://pages.cs.wisc.edu/~beechung/icml11-tutorial/
• http://ijcai-11.iiia.csic.es/files/proceedings/Tutorial%20IJCAI%202...
• http://muricoca.github.io/crab/tutorial.html (using Python)

Collaborative Filtering

• www.cs.cmu.edu/~wcohen/collab-filtering-tutorial.ppt

Large Scale Machine Learning

• http://i.stanford.edu/~ullman/pub/ch12.pdf
• http://www.sanjivk.com/EECS6898/ (introduction to class)
• (lectures) http://www.sanjivk.com/EECS6898/lectures.html
• http://techtalks.tv/talks/introduction-5/57923/

Machine Learning 201

• Advanced Machine Learning Course (CMU)
• Lecture 1: Machine Learning With Scikit-Learn
• Lecture 2: Machine Learning With Scikit-Learn
• Lecture 3: Machine Learning from the Boston Python User Group
• Andrew Ng’s Standford ML Class
• An Introduction to Machine Learning
• Andrew Ng’s Coursera Class Wiki
• Koller's PGM course on Coursera (requires solid prob. background)
• The Machine Learning Library
• JMLR
• CMU Google Slides
• NN Course

Deep Learning:

• Deep Learning - Very wide grasp resource about everything
• Juergen Schmidhuber's home page - Different perspectives of NNs with theoretical view as well
• Home Page of Geoffrey Hinton - And the Father of DL
• Neural Network FAQ, part 1 of 7: Introduction - General sense NN FAQ
• Page on lear.inrialpes.fr - INRIA Deep Learning Notes tutorial
• Page on nyu.edu:21991 - very detailed examples on real datasets
• Hinton's NN lectures at Coursera

Sparse Coding (new):

• ECCV10 tutorials
• CVPR10 tutorials

Some good articles on working with the command line:

• command line nuggets for data science (article focuses on unix but ...
• intro to the command line
• 7 Command Line Tools for Data Scientists 

R:

• R One pagers
• R Time Series
• R Statistical And Machine Learning Task View

Python:

• Pylearn2 Deeplearning Library
• IPython Notebooks on Various Topics

Other (internal, DSC) links

• Jackknife logistic and linear regression for clustering and predict...
• Practical illustration of Map-Reduce (Hadoop-style), on real data
• A synthetic variance designed for Hadoop and big data
• Fast Combinatorial Feature Selection with New Definition of Predict...
• Big data is cheap and easy
• My thoughts on big data and data science: no, it's not hype
• Facebook missing revenue because of poor data science integration
• A little known component that should be part of most data science a...
• 11 Features any database, SQL or NoSQL, should have
• Clustering idea for very large datasets
• Interesting database questions
• When data flows faster than it can be processed
• Correlation and R-Squared for Big Data
• Nasty data corruption getting exponentially worse with the size of ...
• SQL to NoSQL translator
• An extensive glossary of big data terminology
• Building better search tools: problems and solutions
• Marrying computer science, statistics and domain expertize
• From chaos to clusters - statistical modeling without models
• When a data glitch turns great data into worthless gibberish
• New pattern to predict stock prices, multiplies return by factor 5
• Internet Topology - Massive and Amazing Graphs
• What Map Reduce can't do
• Excel for Big Data
• Fast clustering algorithms for massive datasets
• Source code for our Big Data keyword correlation API
• 53.5 billion clicks dataset available for benchmarking and testing
• The curse of big data
• How to detect a pattern? Problem and solution
• Hidden decision trees revisited