Diamensionality Reduction

DR_123.txt

1) Independent component analysis: an introduction http://u.cs.biu.ac.il/~louzouy/courses/seminar/ica.pdf
2) Principal component analysis https://www.utdallas.edu/~herve/abdi-awPCA2010.pdf
3) The Seven Practice Areas of Text Analytics http://datamininglab.com/images/pdfs/PracticalTextMining_Excerpt.pdf
4) Statistical analysis made easy in Python with SciPy and pandas DataFrames http://www.randalolson.com/2012/08/06/statistical-analysis-made-easy-in-python/
5) Pearson Correlation http://www.statsoft.com/Textbook/Statistics-Glossary/P/button/p#Pearson%20Correlation
6) THE PEARSON CHI-SQUARED TEST WITH PYTHON AND R http://connor-johnson.com/2014/12/31/the-pearson-chi-squared-test-with-python-and-r/
7) 7 Techniques for Dimensionality Reduction http://www.dataminingreporting.com/blog/7-techniques-for-dimensionality-reduction 
https://www.linkedin.com/grp/post/35222-5998794653007171586
8) An Introduction to Distributed Machine Learning http://blog.dato.com/an-introduction-to-distributed-machine-learning-1
9) K-nearest neighbors in python https://www.dataquest.io/blog/k-nearest-neighbors/
10) Teaching recurrent Neural Networks about Monet http://blog.manugarri.com/teaching-recurrent-neural-networks-about-monet/
11)