verne.freenode.net changed the topic of #mlpack to: http://www.mlpack.org/ -- We don't respond instantly... but we will respond. Give it a few minutes. Or hours. -- Channel logs: http://www.mlpack.org/irc/
trapz has quit [Quit: trapz]
trapz has joined #mlpack
trapz has quit [Quit: trapz]
witness has joined #mlpack
govg has quit [Ping timeout: 264 seconds]
govg has joined #mlpack
kshitijk has joined #mlpack
KTL has joined #mlpack
govg has quit [Quit: leaving]
Kallor has joined #mlpack
Kallor has quit [Client Quit]
kshitijk has quit [Ping timeout: 264 seconds]
kshitijk has joined #mlpack
trapz has joined #mlpack
Kallor has joined #mlpack
Kallor has quit [Client Quit]
govg has joined #mlpack
govg has quit [Client Quit]
govg has joined #mlpack
kshitijk has quit [Ping timeout: 255 seconds]
govg has quit [Quit: leaving]
udit_s has joined #mlpack
kshitijk has joined #mlpack
< naywhayare>
udit_s: sorry for the slow response
< naywhayare>
if you're working on RBMs, then you should focus on that (unless you have extra time). I was just suggesting decision trees as a neat follow-up project, but there's certainly no hurry, and maybe someone else would be interested :)
kshitijk has quit [Ping timeout: 301 seconds]
KTL has quit [Ping timeout: 256 seconds]
kshitijk has joined #mlpack
kshitijk has quit [Ping timeout: 250 seconds]
kshitijk has joined #mlpack
kshitijk has quit [Ping timeout: 272 seconds]
< udit_s>
naywhayare: oops. sorry. Took off for a while there.
< udit_s>
about the decision trees - I'm actually up for it if it's not too urgent. I've realized I can keep chipping away at such problems over time.
< udit_s>
Talking about a follow-up project, remember the perceptron learning methods ? Looking over the decision stumps got me thinking about Pocket and Prism - the learning policy for the Perceptron.
< udit_s>
I thought extending that, too, would be neat. :)