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!
Why does Java still feel bloated nowadays compared to other languages with garbage collection? - "We were after the C++ programmers. We managed to drag a lot of them about halfway to Lisp." -- Guy Steele. The fundamental problem with Java is that Lisp ...
3 months ago