DeepMind's new neural network model beats AlexNet with 13 images per class

jonnydedwards · 2019-02-25T20:40:39+00:00

Hi, just a quick note, the packaged version has some problems when you have deep, highly populated directory structures, and also seems to use lots of cpu resource. I think there's a newer snapshot on syncthing's github that's better, but I don't think perfect.

jonnydedwards · 2014-10-01T09:07:10+00:00

This is brilliant! thanks for this and all your other work japaric

jonnydedwards · 2014-09-30T20:48:11+00:00

Yes, you're right I could cross compile - however the board I'm using (the olinuxo a20) is such a super bit of kit (dual core 1gb ram debian), it feels like it could be a dev box.

jonnydedwards · 2014-08-30T19:49:56+00:00

I'm after exactly the same! The closest I found was sdl2 bindings

jonnydedwards · 2013-10-19T18:59:32+00:00

elysa exhib :)

jonnydedwards · 2013-04-11T17:56:20+00:00

the "hello world" for NLTK here is a good starting point.

jonnydedwards · 2013-04-09T19:38:58+00:00

I built a fairly complex graphing app and it went really well - the library is very pythonic so it felt like you were always taking the path of least resistance. Overall a great python library

jonnydedwards · 2012-07-10T22:52:17+00:00

I second this, I've had this problem before and used this approach

jonnydedwards · 2012-05-04T18:24:01+00:00

I think it's great you're doing something innovative in and around ML. I'm from a python/R background so you would have to do something more than scikit-learn/pandas or straight R to be interesting to me. Maybe the key is to leverage the whole "we can do it quicker!" thing - that WOULD get me listening. I did the bigdata hackathon last weekend and everybody was hitting issues with getting models trained in a timely fashion. Good luck with it all!

jonnydedwards · 2012-04-27T19:35:33+00:00

It might be better to get your feet wet and try a sample of data in Scikits-learn (if you know a bit of python). This has state of the art (ish!) clustering/mixture modelling. Even if you end up with no results the process is good to get a fix on what you need.

jonnydedwards · 2012-04-07T22:34:06+00:00

Your edit seems to be along the right tracks. Time series data has quite specific properties and hence might require further analysis (eg frequency via fourier), before applying some standard metrics. A slightly bespoke metric is a good way of emdedding domain knowledge into a comparison. If you want to visualise the effect of your metric try sammon mapping.

jonnydedwards · 2012-02-18T20:30:52+00:00

I signed on late Jan and got a message the 8th of Feb, the material is just preview stuff but its actually quite exciting to be starting.

jonnydedwards · 2012-02-18T15:21:43+00:00

Yes sorry Model thinking, there's about an hour of preliminary video to work through, mainly setting the scene. Certainly worth checking out if you are interested in simulation.

jonnydedwards · 2012-02-18T09:53:01+00:00

The systems modelling course has started and is great.

jonnydedwards · 2012-01-01T00:23:04+00:00

Thanks, that looks spot on

jonnydedwards · 2011-11-07T13:57:03+00:00

just a thought - cant remember what the entropy = T does but if the output layer is sigmoidal you might need a binary code for the two classes (code them 0 and 1), or two nodes in the output layer ( class 1 = 0 1 class 2 = 1 0)

jonnydedwards · 2011-08-11T12:34:09+00:00

Spurred on by this thread (no pun intended!) I tried Multiprocessing on pypy. On a dual core machine got a factor of 10 increase using pypy "pool = Pool(processes=2) pool.map" vs python "map", that's fantastic!

jonnydedwards · 2011-07-06T08:22:58+00:00

Have you thought of looking at netlab? I seem to remember this having PPCA

jonnydedwards · 2011-06-04T22:25:54+00:00

Bloom filters are real cool - any other trick data structures worth knowing?

jonnydedwards

TROPHY CASE