This project contains the source files for "Fun Q: A Functional Introduction to Machine Learning in Q".1
Fun Q can be purchased on Amazon and Amazon UK. Books may be purchased in quantity and/or special sales by contacting the publisher, Vector Sigma.
Install q
from Kx System's kdb+ download
page and grab a copy of the
Fun Q source.
$ git clone https://github.com/psaris/funq
The following command starts the q interpreter with all Fun Q libraries loaded and 4 secondary threads for parallel computing.
$ q funq.q -s 4
Any typos or errors are listed here and are incorporated into recent printings of the book.
Swag can be found on the Vector Sigma Teespring site.
Start q with any of the following or read the comments and run the examples one by one.
$ q plot.q -s 4
$ q knn.q -s 4
$ q kmeans.q -s 4
$ q hac.q -s 4
$ q em.q -s 4
$ q nb.q -s 4
$ q tfidf.q -s 4
$ q decisiontree.q -s 4
$ q adaboost.q -s 4
$ q randomforest.q -s 4
$ q linreg.q -s 4
$ q logreg.q -s 4
$ q onevsall.q -s 4
$ q nn.q -s 4
$ q recommend.q -s 4
$ q pagerank.q -s 4
Footnotes
-
More presentations, competitions and books by Nick Psaris can be found at https://nick.psaris.com โฉ