Machine Learning by David L. Richards<\/p>\n
– TenaciousG – a graphs tool with persistence.
\n– Sirb – statistics and erb. A bit of a hack — it monkey patches other classes. It’s kind of cool
\n– TeguGears – Tegu is a never finished gem for machine learning, all in one
\nplace. TeguGears is meant to be its core functionality.<\/p>\n
statisticus – an immature “R” type stats package for Ruby. Don’t use it — it will break — if you can even get it to run. He’s still cleaning it up, and feels that it has potential.
\nrbtree<\/p>\n
A lot of machine learning uses graphs.<\/p>\n
Approaches<\/p>\n
– Ruberl
\n– Rocaml
\n– Blurred Weasel<\/p>\n
Functional style programming has three primary advantages:<\/p>\n
– Composable
\n– Concurrent
\n– Distributed
\n– Etc.<\/p>\n
Fibers. They’re a “new to Ruby” idea — coroutines. They start “paused” and
\nthey are “resumed”.<\/p>\n
– PipelineElement – stolen from Pragmatic Dave (Thomas).
\n– [NeverBlock](http:\/\/espace.com.eg\/neverblock) is an I\/O oriented library. Works with Fibers.<\/p>\n","protected":false},"excerpt":{"rendered":"
Machine Learning by David L. Richards – TenaciousG – a graphs tool with persistence. – Sirb – statistics and erb. A bit of a hack — it monkey patches other classes. It’s kind of cool – TeguGears – Tegu is a never finished gem for machine learning, all in one place. TeguGears is meant to … <\/p>\n