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.

- 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**

- 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/

- 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 - 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

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

**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

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