http://measuringmeasures.com/blog/2010/1/15/learning-about-statistical-learning.html
python(numpy/scipy), R, at-least one functional language Haskell,Clojure or OCaml
http://measuringmeasures.com/blog/2010/1/1/beyond-pagerank-learning-with-content-and-networks.html
http://measuringmeasures.com/blog/2010/6/9/learning-about-network-theory.html
http://measuringmeasures.com/blog/2010/3/12/learning-about-machine-learning-2nd-ed.html
http://www.cs.stanford.edu/people/ang//papers/nips06-mapreducemulticore.pdf
http://brenocon.com/blog/2008/12/statistics-vs-machine-learning-fight/
http://www.inherentuncertainty.org/2010/01/algorithmstheory-culture-vs-machine.html
http://hunch.net/?p=318
http://nlpers.blogspot.com/2010/01/machine-learners-apology.html
http://radar.oreilly.com/2010/06/what-is-data-science.html
http://delivery.acm.org/10.1145/1820000/1810892/p5-vardi.html?key1=1810892&key2=4752783031&coll=DL&dl=ACM&ip=122.167.181.142&CFID=19826789&CFTOKEN=51338947
http://www.quora.com/Educational-Resources/How-do-I-become-a-data-scientist
http://teddziuba.com/2008/05/machine-learning-is-not-as-coo.html
http://petewarden.typepad.com/
http://radar.oreilly.com/2011/04/data-hand-tools.html
http://people.sslmit.unibo.it/~baroni/compling04/UnixforPoets.pdf
http://www.quora.com/What-are-your-swiss-army-knife-one-liners-on-Unix
http://www.stat.cmu.edu/~cshalizi/350/
Introduction to algorithms
Introduction to Linear Algebra
Introduction to probability theory
A Course in Probability theory
First look @ rigorous probability theory
All of statistics: A concise course in Statistical Inference theory
Machine Learning : Tom Mitchell
The elements of Statistical Learning
Introduction to Stochastic Search and Optimization
Introduction to analysis
How to prove it : A Structured approach
"Probability and Random Processes" by Grimmett and Stirzaker
Pattern Recognition and Machine Learning by Christopher Bishop & (Neural Networks for Pattern Recognition)
Judea Pearls' Probablistic Reasoning in Intelligent systems
Probablisitic Graphical Models by D. Koller and N. Friedman
videolectures.net
google video
Few Instructions:
Learn about numerical analysis
Learn statistical analysis
Learn about optimization
Learn about machine learning
Learn about signal detection and estimation
learn about distributed computing
learn about information retrieval
master algorithms and data strucutres
Practice
Courses
Linear Algebra
Information Retrieval
Machine Learning
Data Mining
Papers
Summer Schools:
http://videolectures.net/mlss09uk_cambridge/
http://mlg.eng.cam.ac.uk/mlss09/index.html
Information Retrieval course @ IISC bangalore
python(numpy/scipy), R, at-least one functional language Haskell,Clojure or OCaml
http://measuringmeasures.com/blog/2010/1/1/beyond-pagerank-learning-with-content-and-networks.html
http://measuringmeasures.com/blog/2010/6/9/learning-about-network-theory.html
http://measuringmeasures.com/blog/2010/3/12/learning-about-machine-learning-2nd-ed.html
http://www.cs.stanford.edu/people/ang//papers/nips06-mapreducemulticore.pdf
http://brenocon.com/blog/2008/12/statistics-vs-machine-learning-fight/
http://www.inherentuncertainty.org/2010/01/algorithmstheory-culture-vs-machine.html
http://hunch.net/?p=318
http://nlpers.blogspot.com/2010/01/machine-learners-apology.html
http://radar.oreilly.com/2010/06/what-is-data-science.html
http://delivery.acm.org/10.1145/1820000/1810892/p5-vardi.html?key1=1810892&key2=4752783031&coll=DL&dl=ACM&ip=122.167.181.142&CFID=19826789&CFTOKEN=51338947
http://www.quora.com/Educational-Resources/How-do-I-become-a-data-scientist
http://teddziuba.com/2008/05/machine-learning-is-not-as-coo.html
http://petewarden.typepad.com/
http://radar.oreilly.com/2011/04/data-hand-tools.html
http://people.sslmit.unibo.it/~baroni/compling04/UnixforPoets.pdf
http://www.quora.com/What-are-your-swiss-army-knife-one-liners-on-Unix
http://www.stat.cmu.edu/~cshalizi/350/
Introduction to algorithms
Introduction to Linear Algebra
Introduction to probability theory
A Course in Probability theory
First look @ rigorous probability theory
All of statistics: A concise course in Statistical Inference theory
Machine Learning : Tom Mitchell
The elements of Statistical Learning
Introduction to Stochastic Search and Optimization
Introduction to analysis
How to prove it : A Structured approach
"Probability and Random Processes" by Grimmett and Stirzaker
Pattern Recognition and Machine Learning by Christopher Bishop & (Neural Networks for Pattern Recognition)
Judea Pearls' Probablistic Reasoning in Intelligent systems
Probablisitic Graphical Models by D. Koller and N. Friedman
videolectures.net
google video
Few Instructions:
Learn about numerical analysis
Learn statistical analysis
Learn about optimization
Learn about machine learning
Learn about signal detection and estimation
learn about distributed computing
learn about information retrieval
master algorithms and data strucutres
Practice
Courses
Linear Algebra
Information Retrieval
Machine Learning
Data Mining
Papers
Summer Schools:
http://videolectures.net/mlss09uk_cambridge/
http://mlg.eng.cam.ac.uk/mlss09/index.html
Information Retrieval course @ IISC bangalore
