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Big Data A to ZZ – A Glossary of my Favorite Data Science Things

Here are some of my favorite things about big data and data science, from A to Z (actually, ZZ):

A – Association rule mining

B – Bayes belief networks

C – Characterization

D – Deep learning

E – Ensemble learning

F – Forests (i.e., random forests)

G – Gaussian mixture models

H – Hadoop

I – Informatics

JJ – JSON and JAQL

K – K-anything in data mining

L – Local linear embedding (LLE)

M – Multiple weak classifiers

N – Novelty detection

O – One-class classifier

P – Profiling (data profiling)

Q – Quantified and tracked

R – Recommender engines

S – Support Vector Machines (SVM)

T – Tree indexing schemes

U – Unsupervised exploratory analysis

V – Visual analytics

W – WEKA (Waikato Environment for Knowledge Analysis)

X – XML (specifically Predictive Modeling Markup Language)

Y – YarcData

ZZ – Zero bias, Zero variance

The extended (fully annotated) version of this list, containing additional explanatory detail for each item, can be found at: http://bit.ly/1nuBpk1 

These are just a few of my favorite things in big data science. Please add your own favorites in the comments below.

Follow Kirk Borne on Twitter at @KirkDBorne 

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Comment by Kirk Borne on March 20, 2014 at 12:09pm

The extended version of the post is now live at: http://bit.ly/1g5NcBt

However, the above list is still the only list that has hyperlinks for all of the entries!!

Comment by Omoyele Shodeinde on March 20, 2014 at 10:58am

thanks

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