The F# Journal just published an article about machine learning:
"Many machine learning algorithms benefit from preconditioning the data to reduce a high dimensional problem into a low dimensional problem. For example, by identifying two orthonormal vectors such that projecting the inputs onto those two vectors captures most of the variability in the data set. Principal component analysis is one such algorithm. This article discusses the topic, describes two different solutions and visualizes the results..."
The F# Journal today!
Xavier Leroy's "standard lecture on threads" - Xavier Leroy’s standard lecture on threads post from the caml-list in 2002 seems to have disappeared from the INRIA archives so I am reproducing it here fo...
1 week ago