Small Group Subproblems: Difference between revisions

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*Kinects (Jared, Praveen)
*Kinects (Jared, Praveen)
**Get another kinect and do awesome shit with it.
**Get another kinect and do awesome shit with it.
*Noisebrain(Jared, Mike)
**Install sensors all over Noisebridge.** (need to deal with some privacy concerns first)
***IR? PIR? Visual spectrum? Sonar? Decibel level? Audio seems like privacy landmine.
**We can train it to learn about what's going on in Noisebridge, for example:
***How many people are in the space?
***What sort of activities are happening? Classes? Working? Hacking? Construction?
***What parts of the space are being used? Main Hall? Church? Turing? Kitchen?
***Where is there motion? Where are things out of place?
**Application ideas for the Noisebrain once working:
***Feed this information into [[Noise-Bot]] in addition to it's on-board information.
***Could provide additional context for Music Recommendation project below.
***Neat widgets for Noisebridge website showing what's up.
*Music Recommendation System (Jared)
*Music Recommendation System (Jared)
**Given different people in a space (who voluntarily "checkin"), and a jukebox, play music that appeals to their tastes.
**Given different people in a space (who voluntarily "checkin"), and a jukebox, play music that appeals to their tastes.
**Hard part is data gathering
**<strike>Hard part is data gathering</strike> We are just use last.fm [http://www.last.fm/download#content_ipod scrobbler] & [http://ws.audioscrobbler.com/1.0/user/jareddunne/recenttracks.rss rss feeds].


TODOs:
TODOs:
*Put together a github project
*Put together a github project
*Key is to have a bunch of projects going on at the same time so people can work on whatever they like at a given time.
*Key is to have a bunch of projects going on at the same time so people can work on whatever they like at a given time.

Revision as of 00:52, 17 February 2011

Joe H proposed that we come up with some smaller problems that allow people to interactively solve them in short periods of time in ML meetups. We can construct a git hub project for them, create a skeleton project, and use issue tracking to list the problems and work on them. Here we list these problems and plan to build them out.

  • Time Series Data (Erin)
  • Rock Climbing (Joe H)
    • Rock climbing data analysis
    • Generate predictive system for how much someone should climb based on how they're doing that week.
    • Noted that amount of deep sleep can be correlated to mood, which can be correlated to climbing.
    • Suggestion: we all track one aspect of our daily routines and combine it into one big dataset.
  • 4square Checkins (Joe H)
    • Use 4square checkins to find out what would be the best time to visit a place in a region.
  • Education Learning Problem (Tom)
    • Determine how people learn over time.
    • Figure out how difficult questions are, what kind of knowledge they test
    • Determine how good are people at certain types of knowledge.
  • Auditory Brain Cells (Mike S)
    • Soon to be posted data on crcns.org of auditory brain cells.
    • Figure out how to predict brain cell output.
  • Deep Belief Networks for Images/Sounds (Mike S)
    • Train deep belief networks on images, project output to monitor to see what network is "thinking"
    • Do same for sounds
    • Use auto-encoders to recall memories based on new input
  • Kinects (Jared, Praveen)
    • Get another kinect and do awesome shit with it.
  • Noisebrain(Jared, Mike)
    • Install sensors all over Noisebridge.** (need to deal with some privacy concerns first)
      • IR? PIR? Visual spectrum? Sonar? Decibel level? Audio seems like privacy landmine.
    • We can train it to learn about what's going on in Noisebridge, for example:
      • How many people are in the space?
      • What sort of activities are happening? Classes? Working? Hacking? Construction?
      • What parts of the space are being used? Main Hall? Church? Turing? Kitchen?
      • Where is there motion? Where are things out of place?
    • Application ideas for the Noisebrain once working:
      • Feed this information into Noise-Bot in addition to it's on-board information.
      • Could provide additional context for Music Recommendation project below.
      • Neat widgets for Noisebridge website showing what's up.
  • Music Recommendation System (Jared)
    • Given different people in a space (who voluntarily "checkin"), and a jukebox, play music that appeals to their tastes.
    • Hard part is data gathering We are just use last.fm scrobbler & rss feeds.

TODOs:

  • Put together a github project
  • Key is to have a bunch of projects going on at the same time so people can work on whatever they like at a given time.